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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build next-generation data stack.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll:
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals
Requirements:
7+ years as a BI Engineer or Data Engineer, with 2+ in a technical leadership or architect role
Proven experience managing complex data warehouses that serve multiple products and entire organizations
Strong expertise in data modeling, ELT development, and data warehouse methodologies
Advanced SQL skills and hands-on experience with Snowflake or similar cloud-native data warehouse platforms
Extensive experience with dbt for data transformation and modeling
Python and software development experience (a strong plus)
Excellent communication skills - you can mentor technical team members and explain complex data concepts to business stakeholders
Ready to work in an office environment most days of the week
Enthusiasm about learning and adapting to the exciting world of AI - a commitment to exploring this field is a fundamental part of our culture
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group in TLV. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization
דרישות:
8+ years of experience in data-related roles such as Data Engineer, Data Infrastructure Engineer, BI Engineer, or Machine Learning Platform Engineer, with significant experience in at least two of these areas
A B.Sc. in Computer Science or a related technical field (or equivalent experience)
Extensive expertise in designing and implementing Data Lakes and Data Warehouses, including strong skills in data modeling and building scalable storage solutions
Proven experience in building large-scale data infrastructures, including both batch processing and streaming pipelines
A deep understanding of Machine Learning infrastructure, including tools and frameworks that enable Data Scientists to efficiently develop, deploy, and maintain models in production, an advantage
Proficiency in Python, Pulumi/Terraform, Apache Spark, AWS, Kubernetes (K8s), and Kafka for building scalable, reliable, and high-performing data solutions
Strong knowledge of databases, including SQL (schema design, query optimization) and NoS המשרה מיועדת לנשים ולגברים כאחד.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Data Engineer to take ownership of our evolving data platform.
Our data environment is entering a significant growth phase. We are strengthening our Redshift-based warehouse, expanding our transformation capabilities with dbt, and investing in modern engineering standards across the stack.
In parallel, we are building a dedicated application layer for delivering data products. This role is responsible for designing and owning the data foundations that support it.
AI-assisted development is not a side experiment. It is a core part of how we engineer. We expect this role to actively leverage advanced AI development tools as part of daily work, accelerating design, implementation, validation and documentation while maintaining strong architectural judgment and production-level quality.
This position requires architectural thinking, long-term platform vision and the ability to lead complex initiatives from design through production in an AI-augmented engineering environment.
What You Will Do:
Own the architecture and evolution of our cloud-based Data Warehouse.
Lead complex data initiatives end to end, from requirements definition and technical design through implementation, deployment and post-production optimization.
Apply AI-assisted development workflows to improve engineering velocity, code quality and system reliability.
Design and evolve transformation standards and modeling practices using dbt as a strategic layer within the team.
Architect the data foundations that power our data-driven applications.
Translate business needs into structured, production-grade data solutions.
Drive technical standards, consistency and engineering discipline across the data stack.
Take full accountability for delivery, stability and long-term scalability of the systems you build.
Requirements:
8+ years of experience in Data Engineering with strong focus on modern cloud-based DWH architecture.
Proven experience leading projects end to end in production data environments.
Deep production experience with Redshift, dbt and orchestration frameworks such as Airflow.
Strong SQL expertise and solid understanding of dimensional modeling and transformation best practices.
Practical, daily experience using AI development tools as part of your engineering workflow.
Ability to critically evaluate AI-generated output and maintain high architectural and production standards.
Strong system design capabilities and full ownership mindset.
Experience supporting data products or application-facing data environments.
Ability to balance speed with quality and long-term architectural thinking.
This position is open to all candidates.
 
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04/05/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Staff Data Platform Engineer to join our Engineering team and lead the evolution of our next-generation data platform. In this high-impact role, you will operate as a player-coach: you will be the technical visionary responsible for designing the ecosystem, while remaining deeply hands-on to implement scalable, secure, and intelligent solutions that power everything from operational reporting to advanced GenAI applications.
You will bridge the gap between complex business requirements and technical execution, advocating for a data-first culture. This role offers a clear growth path: while it currently starts as an individual contributor position, it has the potential to evolve into a leadership role.
About the Role:
Architecture & Hands-on Execution: Design and actively build a comprehensive data platform. You will not just oversee infrastructure; you will write the core code and build tools that support diverse workloads-from operational reporting to complex analytical queries.
Strategic & Technical Delivery: Partner with product managers to translate business objectives into technical strategies, then lead the engineering effort to deliver them.
Technology Evaluation: Continuously evaluate, prototype, and select best-in-class technologies to future-proof our data stack.
Technical Leadership & Mentorship: Act as a primary advocate for platform adoption. You will foster a community of practice around data engineering, mentoring senior and mid-level engineers to elevate the team's technical bar.
Governance & Quality: Implement and automate robust frameworks for Data Discovery, Quality, and Governance, ensuring solutions are trustworthy and compliant with financial regulations.
Requirements:
Experience: 8+ years of hands-on experience in Data Engineering and Architecture, with a track record of building and shipping platforms at scale.
Experience with modern big data platforms such as Snowflake, Databricks, or similar technologies.
Hands-on experience with Data infrastructure experience (Orchestration, scalability, reliability, and cloud architecture).
Data Movement & Integration: Deep understanding of data movement strategies, including high-frequency batching, CDC, and real-time event streaming.
Technical Depth: Deep understanding of database internals. High proficiency in Python and SQL. You can dive into code when necessary to solve complex issues.
Modeling & Architecture: Strong know-how in dimensional modeling and schema design (relational and NoSQL), with proven experience implementing Data Warehouse or Lakehouse architectures.
GenAI & RAG Expertise: You have practical experience architecting and building RAG (Retrieval-Augmented Generation) pipelines, with specific knowledge of Vector Databases, Embedding Models, and LLM Orchestration frameworks.
Business Acumen: A strong ability to understand business objectives and translate them into technical strategies that drive tangible value.
Leadership and Communication: As this is a central role in the product tech organisation, you will need a strong ability to influence engineering teams and drive consensus without direct authority. You must have excellent communication skills to explain complex architectural concepts to C-level stakeholders and non-technical partners.
This position is open to all candidates.
 
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10/05/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
We are at a pivotal stage in building and scaling our data domain, and we are looking for a Data Engineer to join our growing BI team. This role goes beyond building pipelines. You will help shape our data platform as a shared product - supporting analytics, reporting, and decision-making across key company data domains such as Product, Sales, HR, and others. Your work will directly influence how stakeholders interact with data today and how the platform evolves in the years ahead.

What Youll Be Doing
Architect & Own: Lead the design and development of scalable data warehouse and BI solutions. You will make early-stage architectural decisions and own their long-term impact.
Infrastructure as a Product: Build core data infrastructure and developer experiences that others rely on, ensuring high availability and system reliability.
End-to-End ELT/ETL: Solve complex integration problems by sourcing data from structured and unstructured sources using Rivery, Python, and optimal ETL patterns.
Data Quality & Governance: Implement frameworks for schema evolution, anomaly detection, and data freshness. You will determine security models based on privacy requirements and evolve governance processes.
Strategic Collaboration: Partner with Engineers, Product Managers, and Data Analysts to conceptualize data needs and represent key insights in a meaningful way.
Optimization: Assist in owning production processes, optimizing complex code through advanced algorithmic concepts to manage operational cost-benefit tradeoffs.
Requirements:
Experience: 5+ years of experience in Data Engineering, Infrastructure, or Platform Engineering (ideally in organizations operating at a meaningful scale).
Technical Mastery: 5+ years of hands-on experience with Python and SQL. Deep proficiency in data modeling (Star/Snowflake schema) and DWH methodologies.
Cloud & Tools: Proven experience with Snowflake and AWS. Familiarity with Rivery or similar orchestration tools (like DBT) is a major advantage.
Production-First Mindset: Track record of leading data initiatives end-to-end from design and building to shipping and operating production flows.
Analytical Rigor: Ability to triage issues, resolve data quality problems, and design systems that handle system complexity with ease.
Education: Bachelors degree in Computer Science, Computer Engineering, or a relevant technical field.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.

This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutions-including the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.

What Youll Do

Architecture & Strategy
Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.

Engineering & Delivery
Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.

Leadership & Collaboration
Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.
Requirements:
What Were Looking For:
6-10+ years of experience in Data Engineering, with demonstrated architectural ownership.
Expert-level experience with Snowflake (mandatory), including performance optimization, data modeling, security, and ecosystem components.
Expert proficiency in SQL and strong Python skills for pipeline development and automation.
Experience with modern orchestration tools (Airflow, Dagster, Prefect, or equivalent).
Strong understanding of ELT/ETL patterns, distributed processing, and data lifecycle management.
Familiarity with streaming/event technologies (Kafka, Kinesis, Pub/Sub, etc.).
Experience implementing data quality, observability, and lineage solutions.
Solid understanding of cloud infrastructure (AWS, GCP, or Azure).
Strong background in DataOps practices: CI/CD, testing, version control, automation.
Proven leadership in driving architectural direction and mentoring engineering teams.

Nice to Have:
Experience with data governance or metadata management tools.
Hands-on experience with DBT, including modeling, testing, documentation, and advanced features.
Exposure to machine learning pipelines, feature stores, or MLOps.
Experience with Terraform, CloudFormation, or other IaC tools.
Background designing systems for high scale, security, or regulated environments.

Additional Skills:
Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Release Management, Security-First Mindset, User Experience (UX).
This position is open to all candidates.
 
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04/05/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're hiring a Data Engineer to join our growing team of analytics experts in order to help & lead the build-out of our data integration and pipeline processes, tools and platform.
The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
The right candidate must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our companys data architecture to support our next generation of products and data initiatives.
In this role, you will be responsible for:
Create ELT/Streaming processes and SQL queries to bring data to/from the data warehouse and other data sources.
Establish scalable, efficient, automated processes for large-scale data analyses.
Support the development of performance dashboards & data sets that will generate the right insight.
Work with business owners and partners to build data sets that answer their specific business questions.
Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization.
Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
Own the data lake pipelines, maintenance, improvements and schema.
Requirements:
BS or MS degree in Computer Science or a related technical field.
3-4 years of Python / Java development experience.
3-4 years of experience as a Data Engineer or in a similar role (BI developer).
3-4 years of direct experience with SQL (No-SQL is a plus), data modeling, data warehousing, and building ELT/ETL pipelines - MUST
Experience working with cloud environments (AWS preferred) and big data technologies (EMR,EC2, S3 ) - DBT is an advantage.
Experience working with Airflow - big advantage
Experience working with Kubernetes - advantage
Experience working with at least in one of the big data environments: Snowflake, Vertica, Hadoop (Impala/Hive), Redshift etc - MUST
Experience working with Spark - advantage
Exceptional troubleshooting and problem-solving abilities.
Excellent verbal/written communication & data presentation skills
This position is open to all candidates.
 
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4 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
We are looking for an experienced and passionate Data Engineer to join the Data Engineering Team in our rapidly growing TLV R&D site!
You will be instrumental in maintaining current pipelines and expanding our data semantic layer to support both traditional analytics and our future AI/ML initiatives.
Responsibilities include working alongside developers from the BI and Backend teams, architects and business decision makers in order to implement data pipelines and improve data architecture and infrastructure.
The Data Engineering Team focuses on building long term, scalable self-service solutions for the organizational growing data needs.
What You'll Do:
Design & Build Robust Pipelines: Develop, deploy, and maintain scalable, highly reliable, and idempotent ELT data pipelines using Python and orchestration tools like Airflow.
Own the Data Model: Lead data transformation and modeling efforts within our cloud data warehouse (e.g., Snowflake, AWS) using dbt, ensuring adherence to modern analytics engineering best practices (modularity, DRY principles, and clear separation of staging and data marts).
Expand the Semantic Layer: Architect and grow our centralized semantic layer to establish a "single source of truth" for business metrics, powering both traditional BI dashboards and upcoming AI initiatives.
Champion Data Quality & Reliability: Implement rigorous data validation, testing, and monitoring to ensure data integrity and build trust with downstream consumers.
Enable Self-Service Analytics: Design intuitive, long-term data infrastructure solutions that empower business stakeholders, analysts, and developers to easily and independently query organizational data.
Cross-Functional Collaboration: Partner closely with Backend developers, BI analysts, architects, and business decision-makers to translate complex business requirements into efficient technical architectures.
Requirements:
Bachelors degree in CS or other relevant field.
3+ years of proven experience as a Data Engineer, Analytics Engineer, or similar role.
Strong proficiency in Python, particularly for data processing and pipeline orchestration.
Experience in Data Modeling using dbt or equivalent.
Experience with Data Warehouse technologies like Snowflake, BigQuery, Redshift ,etc.
Experience with Orchestration platforms like Airflow, Luigi, Dagster, etc.
Experience with Semantic Data Layer technologies like MetricFlow, Cube or others.
Experience in working and delivering end-to-end projects independently.
Experience with at least one cloud provider, preferably AWS.
Strong written and verbal skills in Technical English.
Nice-to-Have:
Experience with ELT platforms like dlt, Fivetran, Airbyte, etc.
Experience with Data Validation and Testing using dbt, Great Expectations or others.
Familiarity with DB internals, design considerations and management.
Familiarity with containerized deployments with K8s.
Familiarity with Event Streaming platforms like Kafka, Redpanda, etc.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
we are looking for a Data Engineer.
As a Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and ore.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.
20718
Requirements:
Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.
Minimum of 3 years of experience as a Data Engineer or a similar role, with a consistent record of successfully delivering ML/Data solutions
You have built production data pipelines in the cloud, setting up data-lake and server-less solutions; ‌ you have hands-on experience with schema design and data modeling and working with ML scientists and ML engineers to provide production level ML solutions.
You have experience designing systems E2E and knowledge of basic concepts (lb, db, caching, NoSQL, etc)
Strong programming skills in languages such as Python and Java.
Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.
Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.
Experience with Data Warehousing and ETL/ELT pipelines
Experience in data processing for large-scale language models like GPT, BERT, or similar architectures - an advantage.
Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.
Experience with experimental design, A/B testing, and evaluation metrics for ML models - an advantage.
Experience of working on products that impact a large customer base - an advantage.
Excellent communication in English; written and spoken.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8627494
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מודים לך שלקחת חלק בשיפור התוכן שלנו :)
4 ימים
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Analytics Engineer to help design and build the engineering foundation that powers analytics across the organization.
Our goal is to create a modern data environment where analytics development is fast, reliable, scalable, and increasingly automated. This includes building strong data warehouse foundations, scalable modeling layers, and introducing AI-powered tools and automation that accelerate how data products are built and used.
In this role, you will be part of an analytics squad, working closely with analysts and business stakeholders while building the infrastructure, automation frameworks, and intelligent tooling that enable analytics to scale across the organization.
This is a unique opportunity to help build the next generation of the data organization.
Key Responsibilities:
Lead AI adoption in the analytics platform, building tools and workflows that automate analytics development, dashboards, and data exploration
Design and build scalable data warehouse models and transformation layers
Build and optimize ETL pipelines and core analytics infrastructure (Bronze / Silver)
Improve performance, reliability, and scalability of the analytics platform
Develop automation and internal tools that accelerate analytics workflows
Enable self-serve data access across the company through semantic layers and reusable datasets
Collaborate with analysts and business teams within an analytics squad
Requirements:
6+ years of experience in Data Engineering and Analytics Engineering roles, building modern data warehouses and analytics platforms using technologies such as BigQuery, dbt, and Python
Experience with workflow orchestration (Dagster, Airflow, or equivalent) and building reliable, observable data pipelines
Hands-on experience using AI coding platforms and tools to automate data engineering and analytics workflows
Strong engineering practices including version control (Git), testing, code reviews, and CI/CD
Experience building automation systems and internal tools for data teams
Experience working closely with analysts, product teams, and business stakeholders in analytics-driven environments
Strong problem-solving skills with a builder mindset
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8654363
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סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
21/04/2026
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are searching for a Senior Data Engineer to join our growing team in Tel Aviv and serve as a cornerstone of data evolution. We need an experienced, high-impact engineer ready to elevate our infrastructure from "functional" to "world-class."

As a pivotal member of the team, you wont just build pipelines; you will architect the future of our data ecosystem. Were looking for someone who obsesses over query latency, high-performance analytics, and cost-efficiency - someone who views data integrity as non-negotiable and thrives on turning complex event streams into elegant, scalable models.

Responsibilities
Lead the end-to-end data strategy, evolving our event-driven architecture to ensure seamless, low-latency data flow across the organization.
Design and implement robust, scalable data models that serve as the "single source of truth" for the entire organization.
Act as our internal Snowflake expert - optimizing performance and cost through best practices in clustering, materialized views, and warehouse management.
Build and maintain sophisticated ELT/ETL pipelines that transform raw event data into actionable insights, with a heavy focus on reliability and observability.
Proactively identify infrastructure bottlenecks and re-engineer processes to handle increasing scale without breaking a sweat.
Partner closely with Product and Engineering teams to translate business needs into technical reality, while mentoring analysts and peers on high-quality SQL and architectural standards.
Requirements:
5+ years of experience in Data Engineering, ideally within high-scale or high-growth environments.
5+ years of hands-on coding experience in Python or Node.js.
Deep experience with modern data warehouses and relational databases (e.g., Snowflake, BigQuery, PostgreSQL, or MySQL).
Deep expertise in Snowflake (internals, optimization, and credit management) is a significant advantage.
A masters grasp of data modeling principles and a passion for creating clean, documented, and reusable data structures.
A proactive team player who thrives in time-sensitive, high-volume environments and can communicate complex technical concepts clearly.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8619443
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