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Location: Rosh Haayin
Job Type: Full Time
We are looking for a talented and experienced Mid-Level Data Engineer with a passion for data and cloud technologies to join our team. In this role, you will be a key player in designing, developing, and maintaining our AWS and Databricks-based data platform. You will bridge the gap between robust Data Engineering, Database Administration (DBA), and high-performance Analytics Engineering.

The ideal candidate understands the Lakehouse architecture, has experience managing modern cloud data warehouses like Snowflake, and possesses the ability to build scalable ETL pipelines that drive data-driven business decisions.

Key Responsibilities

End-to-End Pipelines: Develop and maintain complex ETL/ELT pipelines using Python/PySpark on the Databricks platform, as well as loading and transforming data within Snowflake.
Data Architecture: Implement and manage data layers following the Medallion architecture (Bronze, Silver, Gold) using Delta Lake.
Optimization & Analytics: Set up and manage Databricks SQL Warehouses, perform query optimization, and utilize internal visualizations for rapid data exploration.
Cloud Infrastructure: Leverage AWS cloud services to manage data storage, compute resources, and secure data movement.
DBA & Performance Tuning: Act as a custodian for our data platform-managing indexing, clustering, vacuuming, and performance tuning across both Delta Lake and relational/warehouse environments to ensure cost-efficiency and high speed.
Data Modeling: Design data models (Star Schema / Snowflake) in the Gold layer to ensure optimal performance for BI tools (e.g., Power BI, Tableau).
Data Governance: Manage metadata, permissions, and lineage using Unity Catalog and platform-specific access controls.
Quality Control: Implement automated Data Quality tests as an integral part of the CI/CD data pipelines.
Requirements:
5+ years of experience as a Data Engineer or Data Engineer/DBA - Must.
Strong hands-on experience with the AWS ecosystem (S3, IAM, EC2, etc.) and modern cloud data warehouses, specifically Snowflake.
At least 1 year of intensive, hands-on experience with the Databricks platform (including Notebooks and Workflows).
High proficiency in PySpark (or Spark Scala).
Expertise in writing complex SQL (Window Functions, CTEs) alongside DBA-level performance tuning (query profiling, indexing, partition pruning).
Technical Knowledge: Practical experience with Delta Lake, file formats (Parquet), and working with Cloud Storage (AWS S3 / Azure ADLS).
Modeling: Proven experience in designing Fact and Dimension tables.
This position is open to all candidates.
 
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Location: Rosh Haayin
Job Type: Full Time
We are looking for a highly skilled and visionary Senior Machine Learning Engineer to lead the architecture, design, and deployment of enterprise-grade AI/ML projects on AWS. In this role, you will take full technical ownership of advanced AI initiatives, leveraging both native managed services (such as Amazon SageMaker and Bedrock) and custom-built GenAI models to deliver transformative predictive insights and automation to our customers.

As a Senior ML Engineer, you will bridge the gap between complex data engineering and state-of-the-art data science. You will drive the design of scalable MLOps architectures, optimize high-volume data pipelines, and act as a trusted technical advisor to our clients. You will work closely with solutions architects, project managers, and data scientists, while also mentoring junior and mid-level engineers to elevate the team's technical capabilities.

Responsibilities

Architect and Lead ML Solutions: Spearhead the end-to-end architecture, development, and production deployment of robust Machine Learning models, including advanced predictive analytics, NLP, and Generative AI/RAG systems.
Enterprise MLOps & Automation: Define, design, and implement enterprise-grade MLOps strategies. Establish CI/CD pipelines for ML, automated model training, monitoring, versioning, and governance at scale.
AWS AI/ML Mastery: Architect innovative solutions leveraging AWS AI/ML managed services (e.g., SageMaker, Bedrock) to accelerate time-to-market while ensuring high performance and cost-efficiency.
Advanced Data Engineering: Lead the design of highly scalable infrastructure for extracting, transforming, and loading (ETL) data from diverse sources to support complex ML feature stores and model training.
Unstructured Data & Vector Search: Architect systems for the optimal ingestion, processing, and semantic retrieval of unstructured data (text, images, documents) using Vector Databases (e.g., OpenSearch, Pinecone) and graph-based reasoning.
Strategic Advisory & Collaboration: Act as a trusted AI advisor to external enterprise customers and internal C-level executives. Translate complex business constraints into scalable ML architectures and guide clients through their AI adoption journey.
Technical Leadership & Mentorship: Mentor mid-level and junior engineers, establish coding and architectural best practices, and foster a culture of continuous learning and innovation within the team.
Requirements:
Experience: 5+ years of proven, hands-on experience in a Machine Learning Engineer or highly technical Data Scientist role, with a strong track record of deploying scalable ML models to production environments.
Education: Bachelors (Graduate/Masters highly preferred) degree in Computer Science, Mathematics, Information Systems, or a related quantitative field.
Expert Programming & ML Frameworks: Deep expertise in Python and mastery of modern ML/Deep Learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face).
GenAI & LLM Expertise: Strong hands-on experience with Generative AI architectures, including LLMs, fine-tuning methodologies, domain-specific prompting, and RAG pipelines.
Cloud Architecture: Extensive practical experience architecting solutions on AWS, with deep knowledge of AWS AI/ML Services (SageMaker, Bedrock) and core data/compute services (EC2, EMR, Redshift).
Big Data Ecosystem: Proven experience designing complex data pipelines using big data and stream processing technologies (Spark, Kafka, Kinesis, Elasticsearch, Hadoop).
Database Mastery: Advanced SQL proficiency, deep understanding of relational and NoSQL databases (MySQL, Postgres, DynamoDB), and experience with data modeling at scale.
Customer Facing Leadership: Demonstrated ability to lead technical workshops, manage stakeholder expectations, and drive complex projects with external enterprise customers.
Languages: Fluency in Hebrew and English is essential.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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Location: Rosh Haayin
Job Type: Full Time
Architectural leadership of the enterprise DWH project in an AWS cloud environment. The role focuses on designing robust data infrastructure, establishing the technological roadmap, and enabling seamless large-scale data processing to support BI and AI initiatives.

Key Responsibilities:

Lead the architectural design and implementation of the new enterprise DWH project.
Design, develop, and optimize complex cloud-based data solutions for processing massive datasets.
Select and implement the optimal AWS services (Redshift, Glue, Athena, EMR) and data formats (Parquet, Iceberg) for the core data stack.
Provide technical leadership, mentorship, and professional guidance to the Data Engineering team.
Collaborate closely with development teams, Data Scientists, and end-users to define requirements and deliver innovative Data and AI solutions.
Requirements:
B.Sc. in Computer Science, Engineering, Mathematics, or Statistics.
Proven experience of several years as a Data Architect, with a strong background as a Data Engineer (focusing on Python and Spark).
Deep expertise in planning and designing AWS cloud environments and utilizing data services: Redshift, Glue, Athena, EMR / EMR Serverless, and RDS.
Proven experience in designing complex data pipelines using Airflow, and microservices architecture based on Docker, ECS, and Kubernetes.
Expertise in large-scale analytical data structures, optimizing partitions, and building Data Lakes / DWH using Parquet and Iceberg.
Experience integrating data solutions with leading BI tools (QuickSight, Tableau, PowerBI) for downstream analytics.
Familiarity with Machine Learning platforms and experience designing architectures that support GenAI / Prompt Engineering solutions.
Proven experience in designing complex data pipelines using Airflow / Step Functions, and microservices architecture based on Docker, ECS, and Kubernetes.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8833240
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Location: Rosh Haayin
Job Type: Full Time
Integration into the development team for a core DWH project and various AI projects. Responsibilities include the ingestion of large volumes of new data, followed by deep understanding and analysis of data in close collaboration with Data Scientists. Design, development, and optimization of critical, diverse, and large-scale data pipelines - in both cloud and on-premise environments.



Key Responsibilities:

Take responsibility for the ingestion of large volumes of new data.
Conduct deep understanding and examination of data in close collaboration with Data Scientists.
Design and develop critical, diverse, and large-scale data pipelines and processes.
Deploy and optimize data solutions across both cloud and on-premise environments.
Requirements:
B.Sc. in Computer Science, Engineering, Mathematics, or Statistics - Mandatory.
3+ years of experience as a Data Engineer.
3+ years of development experience in Python - Mandatory.
Hands-on experience with Object-Oriented Programming (OOP).
Hands-on experience with Spark for large-scale data processing - Mandatory.
Hands-on experience with dbt.
Experience building and maintaining data pipelines using tools like Airflow or Kubeflow.
Practical experience and understanding of Docker, and container platforms such as ECS / Kubernetes.
Understanding of optimization techniques and working with advanced data formats, emphasizing Parquet and Iceberg (as well as Avro, HDF5, Delta Lake).
Hands-on experience with AWS data services (including Athena, Glue, EMR / EMR Serverless, Redshift, RDS) - Significant advantage.
Experience working with and integrating BI tools such as QuickSight, Tableau, and PowerBI.
Understanding of Machine Learning concepts and processes.
Practical knowledge of GenAI / prompt engineering solutions - Advantage.
initiative and independence, team player.
Self-learning ability, high analytical skills.
Ability to work under pressure, high level of responsibility and commitment.
Working Interfaces: Development team, production team, end-users.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
24/09/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
You and your team will work primarily with dbt, BigQuery, Looker, and GitHub, while using AI-enabled tools such as Cursor, MCP integrations, n8n, and OpenClaw to automate workflows and scale how the team works.

Success in this role requires strong leadership, technical depth, business understanding, and the ability to turn complex data into clear, actionable recommendations.

Key Responsibilities
Lead, manage, and develop a team of Data Analysts, including setting goals, providing feedback, and supporting their professional growth.
Own the teams priorities and analytical roadmap, ensuring the team focuses on the highest-impact business needs.
Define and drive technical and analytical standards across data modeling, SQL, dbt, testing, code reviews, and BI.
Partner with stakeholders and senior leadership to understand business needs, define KPIs, and translate data into actionable recommendations.
Lead high-impact analyses and guide the development of reliable, scalable data models and Looker dashboards.
Ensure data quality and lead investigations into anomalies, tracking issues, and inconsistent metrics.
Drive AI-native ways of working by turning repeatable analyses and processes into reusable, automated workflows.
Stay hands-on with data, code, and analysis when tackling complex or high-impact problems.
Requirements:
5+ years of experience in business, growth, or data analytics within a fast-paced SaaS or web company, including 2+ years of direct people management experience leading a team of Data Analysts.
Strong business understanding and the ability to translate business needs into clear analytical priorities and actionable insights.
Strong technical leadership and experience establishing analytics and engineering best practices.
Advanced SQL and production experience with dbt, including data modeling, testing, lineage, and CI.
Experience with Git-based development and code review workflows.
Experience building decision-oriented dashboards in Looker or a comparable BI platform.
Practical experience using AI agents in analytical or engineering workflows.
Excellent communication and stakeholder-management skills, with the ability to work effectively with both technical and non-technical teams.
A proactive, hands-on approach and the ability to prioritize effectively in a fast-moving environment.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8832902
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
24/09/2026
Location: Ramat Gan
Job Type: Full Time
We are looking for a Software Engineer to help design and develop the core services and applications that drive our data capabilities. In this role, you will build high-quality, scalable software; contribute to the architecture of our next-generation data systems; and collaborate with research and product teams to turn cutting-edge ideas into production-ready features.
Responsibilities:
Design, develop, and maintain scalable backend services and components that power our data workflows, analytics, and product features.
Build high-quality internal tools and applications that improve engineering workflows and enable data-driven development across the organization.
Contribute to the architecture and evolution of our new data platform with a strong focus on clean design, testability, maintainability, and performance.
Collaborate closely with security researchers, analysts, and product managers to translate innovative cybersecurity concepts into reliable, production-ready software.
Apply engineering best practices across the stack - including code quality, testing, observability, versioning, and documentation - to ensure system robustness as we scale.
Requirements:
B.Sc Computer Science or a related technical field (or equivalent work experience).
3+ years of experience as a Software Engineer, Backend Engineer, or Data Platform Engineer.
Strong, hands-on development experience in Python as part of a production engineering team.
Experience designing, implementing, testing, and deploying production-grade backend services, including API design, data models, and modular architectures.
Basic understanding of CI/CD practices, automated testing, containerized development, and operating software in production environments.
Experience with K8s & cloud-based environments (GCP preferred) - advantage.
Experience with modern data platform concepts (data lakes, metadata layers, analytical engines) - advantage
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8832850
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
Location: Tel Aviv-Yafo
Job Type: Full Time
As a Principal Data Engineer, you will be integral to the security research group, designing, building, and maintaining the data pipelines and data frameworks that are the backbone of our cyber attack detection capabilities. You will work closely with top security and AI researchers, enabling their work and seeing the direct impact of your contributions on our services and the day-to-day effectiveness of the research team.
Key Responsibilities
Lead the design and implementation of end-to-end, complex data pipelines and data platforms in cloud environment.
Collect, analyze, and translate complex data requirements from various stakeholders including data analysts, developers, and Cyber security researchers.
Develop robust, scalable Cloud based data solutions using Python and distributed processing frameworks such as Apache Beam (Dataflow) , GKE , Spark , etc.
Utilize AI as part of the development cycle, including generating, reviewing, and testing code via prompts.
Model and manage data within cloud MPP databases and data lakes such as BigQuery, Redshift, or Snowflake.
Requirements:
4+ years experience as a Senior Data Engineer / Data engineer lead (Hands-On) / Data architect - working with Cloud environments
Experience in leading and implementing end to end complex Data pipelines and data platforms
Experience with collecting , analyzing and syncing complex data requirements from various data users such as: Data Analysts , Developers , Researchers and Managers
4+ years Experience with Data Modeling using various Data platforms and databases
4+ years Python experience - focused on Data related areas and distributed processing (Experience with at least one of the following:
Spark, GCP DataFlow (Apache Beam), GKE , etc)
Experience with Docker & Kubernetes / GKE
4+ Years experience with Cloud MPP Databases / Data Lakes such as: BigQuery , Redshift , Snowflake , Azure SQL DWH , Azure Kusto
Fluent with SQL
AI:
Using AI as part of the development cycle is second nature for you.
Experience generating code via Prompts and closing the loop by reviewing and testing
Experience writing MCPs , Skills and mds
Soft skills:
Collaborative Mindset: A team-first leader who believes that the best data products are built through collective genius and open communication.
Bridge Builder: Naturally connects the dots between diverse teams-from DevOps to Data Science-to break down silos and streamline data delivery.
Growth-Minded: Approaches feedback as a tool for evolution; possesses the grit to pivot and find the "silver lining" in complex technical setbacks.
Execution Passionate: Genuinely loves the "how" as much as the "what," finding joy in the pursuit of clean code and the deployment of mission-critical pipelines.
Preferred Qualifications
GCP experience
Data science background
Cyber security knowledge.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8832620
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
24/09/2026
Location: Petah Tikva
Job Type: Full Time
We seek an experienced Senior Staff Data Engineer to join our AI and Data Solutions unit and champion an AI-first strategy. You will spearhead the development of Data Lakehouse processes, model core product domains, and define data engineering best practices across the organization. Serving as a technical project lead, you will provide strong direction and collaborate with Data Science, Analytics, R&D, and IT teams to elevate onboarding workflows. This role demands a proactive approach to optimizing system capabilities and driving cross-functional data initiatives.
Key Responsibilities:
Own the design, implementation, and optimization of scalable Data Lakehouse and Data Warehouse architectures across diverse cloud ecosystems.
Spearhead the development of robust ETL/ELT pipelines and data ingestion processes utilizing SQL, Python, PySpark, and DBT.
Apply advanced data modelling techniques to structure complex data assets into optimized facts, dimensions, and partitions.
Partner with cross-functional leadership across data science, analytics, R&D, and IT to identify requirements and improve workflows.
Orchestrate complex data workflows combining tools like Airflow and DBT with advanced Gen-AI development workflows using CloudCode.
Define, document, and popularize data engineering best practices, design patterns, and data quality standards across the unit.
Evaluate and implement modern data technologies spanning vendor-specific and open-source landscapes including GCP, AWS, and Apache Iceberg.
Provide technical direction and hands-on guidance to ensure high-performance execution, reliable pipeline delivery, and proactive problem-solving.
Requirements:
Required Qualifications:
5+ years of experience with advanced data modeling techniques and concepts (e.g., Facts, Dimensions, Partitions).
5+ years of experience designing and implementing end-to-end data ingestion and ETL processes within Data Lakehouse architectures.
5+ years of hands-on experience programming in SQL and Python, PySpark, Java, or Scala.
Demonstrated experience leading technical projects, driving stakeholder alignment, and navigating cross-functional dynamics.
Proven experience working within cloud environments (AWS or GCP), with a strong requirement for AWS.
Deep understanding of the modern data landscape and open-source tools (e.g., Iceberg, DBT, Airflow).
Proven capability in using and orchestrating Gen-AI workflows based on CloudCode and Cursor.
Preferred Qualifications:
Deep expertise in the AWS ecosystem, including Glue, Athena, SageMaker, and EMR.
Advanced experience with Data Warehouse technologies, especially Apache Iceberg or BigQuery.
Leadership or mentorship experience within a data engineering or analytics unit.
Background or domain knowledge in cybersecurity is a strong advantage.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8832126
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
Were hiring an AI Backend Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of AI/ML/Backend engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.
Requirements:
7+ years of experience as a Backend Developer / Data Engineer / ML Engineer
3+ years in a technical leadership role.
Python (Java as an advantage)
Bachelors degree in Computer Science or related STEM field (Masters preferred).
Proven track record of building and deploying AI-based solutions at scale.
Deep expertise with LLMs and ML frameworks (e.g., LangChain, LangGraph, Hugging Face, TensorFlow, PyTorch).
Strong background in system design, cloud-native architecture, and microservices.
Experience with NoSQL and real-time data processing pipelines.
Exceptional leadership, mentorship, and communication skills.
Strategic mindset with the ability to balance hands-on coding and team leadership.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8831946
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דיווח על תוכן לא הולם או מפלה
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שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
23/09/2026
Location: Petah Tikva
Job Type: Full Time
We seek an experienced Senior Staff Data Engineer to join our AI and Data Solutions unit and champion an AI-first strategy. You will spearhead the development of Data Lakehouse processes, model core product domains, and define data engineering best practices across the organization. Serving as a technical project lead, you will provide strong direction and collaborate with Data Science, Analytics, R&D, and IT teams to elevate onboarding workflows. This role demands a proactive approach to optimizing system capabilities and driving cross-functional data initiatives.
Key Responsibilities:
Own the design, implementation, and optimization of scalable Data Lakehouse and Data Warehouse architectures across diverse cloud ecosystems.
Spearhead the development of robust ETL/ELT pipelines and data ingestion processes utilizing SQL, Python, PySpark, and DBT.
Apply advanced data modelling techniques to structure complex data assets into optimized facts, dimensions, and partitions.
Partner with cross-functional leadership across data science, analytics, R&D, and IT to identify requirements and improve workflows.
Orchestrate complex data workflows combining tools like Airflow and DBT with advanced Gen-AI development workflows using CloudCode.
Define, document, and popularize data engineering best practices, design patterns, and data quality standards across the unit.
Evaluate and implement modern data technologies spanning vendor-specific and open-source landscapes including GCP, AWS, and Apache Iceberg.
Provide technical direction and hands-on guidance to ensure high-performance execution, reliable pipeline delivery, and proactive problem-solving.
Requirements:
Required Qualifications
5+ years of experience with advanced data modeling techniques and concepts (e.g., Facts, Dimensions, Partitions).
5+ years of experience designing and implementing end-to-end data ingestion and ETL processes within Data Lakehouse architectures.
5+ years of hands-on experience programming in SQL and Python, PySpark, Java, or Scala.
Demonstrated experience leading technical projects, driving stakeholder alignment, and navigating cross-functional dynamics.
Proven experience working within cloud environments (AWS or GCP), with a strong requirement for AWS.
Deep understanding of the modern data landscape and open-source tools (e.g., Iceberg, DBT, Airflow).
Proven capability in using and orchestrating Gen-AI workflows based on CloudCode and Cursor.
Preferred Qualifications:
Deep expertise in the AWS ecosystem, including Glue, Athena, SageMaker, and EMR.
Advanced experience with Data Warehouse technologies, especially Apache Iceberg or BigQuery.
Leadership or mentorship experience within a data engineering or analytics unit.
Background or domain knowledge in cybersecurity is a strong advantage.
Our
This position is open to all candidates.
 
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8831076
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23/09/2026
Job Type: Full Time
Were looking for a hands-on Data Platform Team Lead to guide a high-performing team in designing, scaling, and operating the infrastructure that powers Chargeflows platform.

This role combines architectural leadership with people management. Youll define the technical direction for our data platform while developing engineers, strengthening execution, and building a culture of ownership and technical excellence.

Youll be responsible for the reliability, performance, security, and cost efficiency of data systems supporting millions of daily transactions and critical product, machine-learning, and analytics use cases. This is a role for someone who can move comfortably between long-term architecture, hands-on technical problem-solving, and day-to-day team leadership.

The impact youll have

Build and evolve the data infrastructure that safeguards our clients revenue and powers critical product, ML, and analytics use cases.
Establish scalable engineering standards and operational practices (reliability, security, governance, and cost efficiency).
Lead and grow a team of data/infrastructure engineers while cultivating technical excellence and psychological safety.

What youll own (Your arena)
Leadership & Mentorship: Lead, mentor, and scale a team of talented data and infrastructure engineers.
Create strong execution rituals: clear ownership, high-quality delivery, feedback loops, and growth plans.
Data Infrastructure & FinOps: Own the architecture and evolution of our modern data stack and platform services.
Drive cloud cost management (FinOps): cost visibility, optimization initiatives, and capacity planning.
High-Performance Engineering: Oversee the design of distributed systems, real-time streaming, and batch pipelines capable of processing millions of daily transactions with minimal latency.
Define technical direction for storage, compute, and data movement patterns (event-driven + lakehouse).
Operational Excellence Champion Infrastructure-as-Code (IaC), CI/CD, and testing practices for infrastructure and data systems.
Establish observability standards (monitoring/alerting, SLOs, incident response, postmortems).
Partner on security compliance and data governance across the R&D organization.
Strategic Collaboration: Act as the bridge between data engineering, product, data science, and core R&D teams to execute cross-functional initiatives.
Translate business goals into platform roadmaps, milestones, and measurable outcomes.
Requirements:
What You Bring
Experience: 6+ years in data platform engineering, data infrastructure, or backend engineering, including 2+ years leading/managing/mentoring engineers.
Strong software engineering: Proficiency in Python (or similar) and modern practices (clean code, CI/CD, testing paradigms).
Data architecture: Extensive experience architecting and operating scalable data lakes/lakehouses, distributed systems, and real-time event-driven architectures.
Cloud-native & IaC: Experience with AWS, GCP, or Azure, plus Docker/Kubernetes and Infrastructure-as-Code (e.g., Terraform).
Databases & storage: Strong knowledge of relational (e.g., PostgreSQL), NoSQL, and analytical databases, including performance optimization, schema design, and cost tuning at scale.
Execution & delivery: Proven track record managing sprint planning, scoping technical projects, and delivering complex infrastructure roadmaps on time.

Nice to Have
Advanced data stack: Apache Iceberg (Lakehouse/S3/Glue), Apache Spark optimization, and big data processing.
Streaming & messaging: Kafka, Kinesis, Flink, Kafka Streams.
Modern tooling: Temporal/Dagster, dbt/DuckDB, Datadog/Grafana, Pydantic.
FinOps & governance: Spot instances/savings plans and compliance frameworks (GDPR/PCI-DSS).
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8830492
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
23/09/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
At our company, business users don't file ticket requests for dashboards. They ask questions in natural language and get answers directly - through Claude, connected to Looker and our other data tools over MCP. Claude is also our primary tool for writing code here.

That only works if what sits underneath is right. This role owns that foundation: the event instrumentation in our products, the pipelines feeding the warehouse, the models that give the data meaning, and the tests that prove it's correct. You're not producing charts - you're making hundreds of self-served answers trustworthy.

It's an engineering role, but not one you can do from behind the data. You'll need to understand the business well enough to know what a metric should mean before you model it.

Responsibilities
Instrumentation - Own product event tracking end-to-end: define the tracking plan with Product, drive implementation with our frontend and backend teams, audit what's actually firing, and build validation that catches regressions at deploy time rather than three months later.
Pipelines and warehouse - Build and operate batch and streaming pipelines into the warehouse; own its transformation layer, performance, data quality monitoring, and alerting.
Semantic layer - Own metric definitions and the modeled layer our AI and BI tooling query against, so core business terms resolve to one thing company-wide. Design models that hold up under open-ended questions, not just the ones you anticipated. Own lineage, documentation, and governance.
Business partnership - Work directly with Product, Sales, Customer Success, and Finance to understand what they're trying to measure, and push back when a proposed metric won't survive contact with reality.
Our stack
Redshift, Looker, Airflow, Kafka, AWS, Kubernetes, Python, SQL, TypeScript - with Claude and MCP as the layer connecting people to all of it.
Requirements:
5+ years building and operating production data infrastructure - pipelines, warehouses, and models you owned end-to-end
Deep SQL and strong dimensional modeling; hands-on with a cloud warehouse (Redshift, Snowflake, BigQuery)
2+ years of Python in production
Airflow or an equivalent orchestrator
Demonstrated ownership of product event instrumentation - tracking plan design, implementation with product engineers, and data quality validation
Able to read application code (TypeScript/Node.js)
Background in engineering or computer science
Advantage: Kafka or equivalent streaming dbt or similar LookML or another semantic layer CI/CD and testing applied to data building data for LLM/agent consumption MCP geospatial data marketplace or high-traffic consumer products
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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עדכון קורות החיים לפני שליחה
8830273
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
22/09/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
Design, build, and maintain robust pipelines feeding both DWH and production processes
Own pipeline orchestration in Apache Airflow end to end, including DAG design, monitoring, alerting, and production reliability
Design the data models behind our core domains and the contracts that downstream consumers depend on
Partner with business analysts, PMs, and business stakeholders to translate product and business questions into stable, qualified, and well-modeled data
Work with a variety of data sources including product events, application data, APIs, operational databases, logs, and third-party systems
Debug and solve data quality, pipeline, performance, and reliability issues
Use and create AI agents and LLM-based tooling to improve development, testing, documentation, and root cause analysis
Be part of the team and adopt effective ways of using AI tools in the engineering workflow.
Requirements:
3+ years in data engineering or a similar data-focused engineering role
Strong hands-on Python and SQL skills, with the ability to write clean, performant, and maintainable code
Proven track record of building and running code in large scale production environments
Deep, hands-on Apache Airflow experience, including ownership of production DAGs at scale
Deep data modeling expertise and the ability to design clean, scalable data assets that hold up as the business changes
Strong business and product orientation. You care about what the metric means, not just whether the job succeeded
Experience working with PMs, analysts, and business stakeholders to understand requirements and build the right data solutions
Practical experience using AI coding agents and LLM-based tools as part of your daily engineering workflow
Experience working with large and varied data sources including product events, application data, APIs, operational databases, logs, and third-party systems
Strong debugging and problem-solving skills around data quality, pipeline failures, performance, and reliability
Nice to have
Experience running data workloads in containerized or Kubernetes-based environments
Experience with large-scale or distributed processing using Spark / PySpark
Experience with query engines such as Trino
Experience with CI/CD and software engineering best practices
Experience building internal tooling or agents on top of LLMs.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8828507
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Location: Ra'anana
Job Type: Full Time
We are seeking an experienced and highly motivated Data Center Manager to lead the planning, operation, growth, and strategic development of our global lab and data center infrastructure. This role combines technical leadership, operational excellence, team management, and long-term capacity planning to support the company's rapid growth and evolving technological needs. Reports To: VP Global IT
The ideal candidate will bring extensive experience in large-scale data center environments, strong networking expertise, and a proven ability to lead teams and manage multiple sites while ensuring high availability, efficiency, and scalability.
Key Responsibilities
Leadership & Team Management
Partner with lab customers to define long term infrastructure roadmaps, anticipate future needs, and align lab growth with business and engineering objectives.
Lead, mentor, and develop a team of data center and lab engineers.
Establish operational standards, processes, and best practices across all lab locations.
Drive a culture of accountability, innovation, and continuous improvement.
Manage resource allocation and prioritize activities to meet business objectives.
Data Center & Lab Operations
Oversee the day to day operation of company labs and data center facilities.
Ensure high availability, reliability, and operational excellence across all environments.
Maintain real time visibility into lab status, capacity, utilization, and health.
Monitor infrastructure components, resource consumption, and workload distribution across the labs.
Provide ongoing operational reporting and status updates to management.
Strategic Planning & Capacity Management
Define and execute the long term growth strategy for the company's lab and data center infrastructure.
Forecast capacity requirements and proactively plan infrastructure expansion.
Monitor utilization trends, workload distribution, and resource consumption.
Optimize infrastructure allocation to maximize efficiency, performance, and scalability.
Develop forward looking plans to support upcoming projects and business initiatives.
Infrastructure Expansion & Projects
Lead the design, deployment, and commissioning of new data centers and lab facilities.
Plan and manage expansion projects for existing sites.
Coordinate infrastructure initiatives across multiple locations and stakeholders.
Ensure projects are delivered on time, within scope, and aligned with business needs.
Manage infrastructure lifecycle planning, including upgrades, replacements, and capacity enhancements.
דרישות:
Must Have
10+ years of experience in data center operations, infrastructure management, or related fields.
Strong hands-on expertise in networking technologies and large scale network infrastructures.
Proven experience managing teams of at least 10 employees in a global company.
Experience managing multiple data center or lab locations simultaneously.
Demonstrated success in capacity planning, infrastructure growth, and operational management.
Experience leading data center construction, expansion, or large scale infrastructure deployment projects.
Strong project management and execution skills.
Excellent leadership, communication, and stakeholder management capabilities.
Ability to operate effectively in a fast-paced, high-growth technology environment.
Nice to Have
Experience with liquid cooling technologies and next-generation data center cooling solutions.
Experience building or operating high density AI, HPC, or large scale compute environments.
Familiarity with infrastructure monitoring, automation, and orchestration platforms.
Experience managing global lab environments supporting R&D and product validation activities.
Success Metrics
High availability and operational stability across all lab and data center environments.
Accurate capacity planning and proactive infrastructure scaling.
Efficient workload balancing and optimal המשרה מיועדת לנשים ולגברים כאחד.
 
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8828137
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Location: Petah Tikva
Job Type: Full Time
We are looking for a strong, hands-on Data Engineer to join our team and play a key role in building our data infrastructure from the ground up. In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases. You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption. This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.
What will your job look like?
Design, build, and maintain robust and scalable data pipelines (batch and real-time) end-to-end.
Design and implement scalable, flexible data architectures to support evolving business needs.
Build and manage data platforms, including data lakes and data warehouses.
Integrate multiple data sources (structured and unstructured) into a unified data platform using batch (ETL) and real-time streaming solutions.
Design and implement efficient data models, schemas, and database structures (SQL / NoSQL).
Develop and implement data quality processes to ensure accuracy, consistency, and reliability.
Monitor, optimize, and troubleshoot data infrastructure to meet performance and SLA requirements.
Requirements:
5+ years of hands-on experience as a Data Engineer, building data systems from scratch in dynamic environments.
Bachelors degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
Strong proficiency in Python and advanced SQL, with solid experience in data modeling.
Proven experience designing and building scalable data pipelines (batch and real-time), including streaming technologies such as Kafka.
Strong experience working with AWS, including services such as S3, Athena and DynamoDB.
Experience working with big data processing frameworks such as Spark, and columnar data formats (e.g., Parquet).
Hands-on experience with workflow orchestration tools such as Airflow.
Strong ownership and execution mindset, with excellent problem-solving skills and high attention to detail, and the ability to collaborate effectively and deliver in ambiguous, fast-paced environments.
Fluent in English.
Nice to have:

Experience with data platform technologies such as Databricks, Snowflake.
Experience building data platforms using modern lakehouse technologies (e.g., Iceberg).
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8827701
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