Data Group Tech Lead, Staff Engineer

3 ימים

Data Group Tech Lead, Staff Engineer

חברה חסויה

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. 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 our data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives us 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 NoSQ המשרה מיועדת לנשים ולגברים כאחד.

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3 ימים

Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were looking for an experienced Data Engineer to join our DataWarehouse team in TLV.
In this role, you will play a pivotal role in the Data Platform organization, leading the design, development, and maintenance of our data warehouse. In your day-to-day, youll work on data models and Backend BI solutions that empower stakeholders across the company and contribute to informed decision-making processes all while leveraging your extensive experience in business intelligence.
This is an excellent opportunity to be part of establishing our state-of-the-art data stack, implementing cutting-edge technologies in a cloud environment.
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:
Lead the design and development of scalable and efficient data warehouse and BI solutions that align with organizational goals and requirements
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into the semantic layer
Develop processes to enforce schema evaluation, cover anomaly detection, and monitor data completeness and freshness
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency
Implement best practices for data warehouse and database performance tuning
Conduct thorough testing of data applications and implement robust validation processes
Collaborate with Data Infra Engineers, Developers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers

Requirements:
3+ years of experience as a BI Engineer or Data Engineer
Proficiency in data modeling, ELT development, and DWH methodologies
SQL expertise and experience working with Snowflake or similar technologies
Prior experience working with DBT
Experience with Python and software development, an advantage
Excellent communication and collaboration skills
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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3 ימים

Data Warehouse Tech Lead

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 our 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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22/02/2026

Senior AI Infra Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were seeking an experienced and skilled Data and AI Infra Engineer to join our Data Infrastructure team and drive the companys data capabilities at scale.
As the company is fast growing, the mission of the data and AI infrastructure team is to ensure the company can manage data at scale efficiently and seamlessly through robust and reliable data infrastructure.
A day in the life and how youll make an impact:
As a Senior Engineer, you are required to independently lead the design, development, and optimization of our data infrastructure, collaborating closely with software engineers, data scientists, data engineers, and other key stakeholders. You are expected to own critical initiatives, influence architectural decisions, and mentor engineers to foster a high-performing team
You will:
Lead the design and development of scalable, reliable, and secure data storage, processing, and access systems.
Define and drive best practices for CI/CD processes, ensuring seamless deployment and automation of data services.
Oversee and optimize our machine learning platform for training, releasing, serving, and monitoring models in production.
Own and develop the company-wide LLM infrastructure, enabling teams to efficiently build and deploy projects leveraging LLM capabilities.
Own the company's feature store, ensuring high-quality, reusable, and consistent features for ML and analytics use cases.
Architect and implement real-time event processing and data enrichment solutions, empowering teams with high-quality, real-time insights.
Partner with cross-functional teams to integrate data and machine learning models into products and services.
Ensure that our data systems are compliant with the data governance requirements of our customers and industry best practices.
Mentor and guide engineers, fostering a culture of innovation, knowledge sharing, and continuous improvement.

Requirements:
7+ years of experience in data infra or backend engineering.
Strong knowledge of data services architecture, and ML Ops.
Experience with cloud-based data infrastructure in the cloud, such as AWS, GCP, or Azure.
Deep experience with SQL and NoSQL databases.
Experience with Data Warehouse technologies such as Snowflake and Databricks.
Proficiency in backend programming languages like Python, NodeJS, or an equivalent.
Proven leadership experience, including mentoring engineers and driving technical initiatives.
Strong communication, collaboration, and stakeholder management skills.
Bonus Points:
Experience leading teams working with serverless technologies like AWS Lambda.
Hands-on experience with TypeScript in backend environments.
Familiarity with Large Language Models (LLMs) and AI infrastructure.
Experience building infrastructure for Data Science and Machine Learning.
Experience collaborating with BI developers and analysts to drive business value.
Expertise in administering and managing Databricks clusters.
Experience with streaming technologies such as Amazon Kinesis and Apache Kafka.

This position is open to all candidates.

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22/02/2026

Tech Lead, AI Infra

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were seeking an experienced and skilled Data and AI Infra Tech Lead to join our Data Infrastructure team and drive the companys data capabilities at scale.
As the company is fast growing, the mission of the data and AI infrastructure team is to ensure the company can manage data at scale efficiently and seamlessly through robust and reliable data infrastructure.
As a tech lead, you are required to independently lead the design, development, and optimization of our data infrastructure, collaborating closely with software engineers, data scientists, data engineers, and other key stakeholders. You are expected to own critical initiatives, influence architectural decisions, and mentor engineers to foster a high-performing team.
You will:
Lead the design and development of scalable, reliable, and secure data storage, processing, and access systems.
Define and drive best practices for CI/CD processes, ensuring seamless deployment and automation of data services.
Oversee and optimize our machine learning platform for training, releasing, serving, and monitoring models in production.
Own and develop the company-wide LLM infrastructure, enabling teams to efficiently build and deploy projects leveraging LLM capabilities.
Own the company's feature store, ensuring high-quality, reusable, and consistent features for ML and analytics use cases.
Architect and implement real-time event processing and data enrichment solutions, empowering teams with high-quality, real-time insights.
Partner with cross-functional teams to integrate data and machine learning models into products and services.
Ensure that our data systems are compliant with the data governance requirements of our customers and industry best practices.
Mentor and guide engineers, fostering a culture of innovation, knowledge sharing, and continuous improvement.

This position is open to all candidates.

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23/03/2026

Senior Backend Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are seeking a Senior Backend Engineer - Data Platform to join our expanding team and play a crucial role in designing, building, and maintaining robust and scalable data pipelines and infrastructure. In this role, you will directly enable data-driven decision-making and support the development and deployment of AI/ML products that power Health.

Youll collaborate closely with engineering, product, and data science teams to ensure our data systems are high-quality, resilient, and scalable as we grow. As a Senior Backend Engineer on our Data Platform team, you will drive efforts to deliver reliable, efficient, and consistent data services across the organization. You will also help enable the rapid development and deployment of advanced features, insights, and AI-driven capabilities that improve outcomes for clinicians and clients.

Who are you?
You are a seasoned backend or data engineer with experience working on production-grade ML/AI-powered products. You thrive in fast-paced, high-ownership environments and are passionate about building scalable and reliable systems. You understand the unique requirements of delivering AI/ML features in production, and you are comfortable working with modern technologies in the LLM/RAG ecosystem.
You pride yourself on delivering high-quality solutions quickly, without sacrificing design or reliability. Youre known for your responsiveness, collaborative spirit, and service-oriented mindset-especially when youre on-call and the stakes are high.How will you contribute?
Design, implement, and maintain scalable and reliable data pipelines and backend systems supporting both operational and analytical needs, with a focus on ML/AI product enablement.
Ensure data processing is optimized for speed, efficiency, and fault tolerance, enabling seamless integration with AI/ML workflows and reliable performance across all our Health products.
Monitor and improve uptime, reliability, and observability of our data infrastructure and pipelines.
Build and maintain systems to ensure data quality, consistency, and usability across the organization, enabling advanced analytics and AI solutions.
Work closely with product and engineering teams to deliver new features rapidly and with a high standard of technical excellence.
Drive innovation in how we build, measure, and optimize data features, backend services, and AI product integrations.
Participate in on-call rotations with a service-oriented approach and fast responsiveness.
Lead scalability efforts to support increasing data volumes, expanding AI/ML initiatives, and new product launches.

Requirements:
What qualifications and skills will help you to be successful?
At least 5 years of experience with Python in backend or data engineering roles, designing and operating large-scale data pipelines, backend services, and data infrastructure in production environments.
Hands-on experience working on ML/AI-powered products in production, with strong understanding of requirements for integrating data platforms with AI features.
Familiarity with modern LLM (Large Language Model) and RAG (Retrieval-Augmented Generation) technologies, and experience supporting their deployment or integration.
Familiar with or have worked with these technologies (or alternatives):
Data Processing & Streaming: Apache Spark, DBT, Airflow, Airbyte, Kafka
API Development: FastAPI, micro-service architecture, SFTP
Data Storage: Data Lakehouse architectures, Apache Iceberg, Vector Databases, RDS
ML/AI: ML/LLM libraries and frameworks (such as Gemini, Hugging Face, etc.)
Cloud Infrastructure: AWS stack (S3, Firehose, Lambda, Athena, etc.), Kubernetes (K8s)
Demonstrated ability to optimize performance and ensure high availability, scalability, and reliability of backend/data systems.
Strong foundation in best practices for data quality, governance, security, and observability.

This position is open to all candidates.

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1 ימים

Senior Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

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.

This position is open to all candidates.

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24/02/2026

Data Engineer II - GenAI

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Data Engineer II - GenAI
20718
Leadership/Team Quote:
This opening is for the Content Intelligence team within the Marketplace AI department.
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
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 more.
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.

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.

This position is open to all candidates.

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24/02/2026

Senior Data Engineer I - GenAI Foundation Models

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Senior Data Engineer I - GenAI Foundation Models
21679
Leadership/Team Quote:
This opening is for the Content Intelligence team within the Marketplace AI department.
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
As a Senior 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 more.
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.

Requirements:
Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.
Minimum of 6 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.

This position is open to all candidates.

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8560108

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2 ימים

Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time and Hybrid work

We are looking for a talented Data Engineer to join our analytics team in the Big Data Platform group.
Job Id: 25380
You will support our product and business data initiatives, expand our data warehouse, and optimize our data pipeline architecture with an AI first attitude.
The ideal candidate is experienced in leveraging AI tools as part of modern data pipeline development, enabling scalable solutions, accelerating delivery, and continuously exploring new approaches and technologies.
The right candidate is excited by the prospect of building the data architecture for the next generation of products and data initiatives.
This is a unique opportunity to join a team full of outstanding people making a big impact on us.
We work on multiple products in many domains to deliver truly innovative solutions in the Cyber Security and Big Data realm.
This role requires the ability to collaborate closely with both R&D teams and business stakeholders, to understand their needs and translate them into robust and scalable data solutions.
Key Responsibilities
Maintain and develop enterprise-grade Data Warehouse and Data Lake environments
Create data infrastructure for various R&D groups across the organization to support product development and optimization
Work with data experts to assist with technical data-related issues and support infrastructure needs
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for scalability
Build and maintain robust ETL/ELT pipelines for data ingestion, transformation, and delivery across various systems
Incorporate AI-assisted tools into data pipeline design, development, and optimization to improve efficiency, scalability, and innovation

Requirements:
B.Sc. in Engineering or a related field
3+ years of experience as a Data Engineer working on production systems
Advanced SQL knowledge and experience with relational databases
Proven experience using Python
Hands-on experience building, optimizing, and automating data pipelines, architectures, and data sets
Experience in creating and maintaining ETL/ELT processes
Strong project management and organizational skills
Strong collaboration skills with both technical (R&D) and non-technical (business) teams
Experience using AI tools as part of the data engineering workflow, with a mindset of experimentation, working at scale, and exploring new technologies
Advantage: Azure data services, Databricks, EventHub, and Spark.

This position is open to all candidates.

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8597003

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09/03/2026

Senior Solutions Engineer - Big Data & Data Infrastructure

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.

Requirements:
2-4 years in software / solution or infrastructure engineering, with 2-4 years focused on building / maintaining large-scale data pipelines / storage & database solutions.
Proficiency in Trino, Spark (Structured Streaming & batch) and solid working knowledge of Apache Kafka.
Coding background in Python (must-have); familiarity with Bash and scripting tools is a plus.
Deep understanding of data storage architectures including SQL, NoSQL, and HDFS.
Solid grasp of DevOps practices, including containerization (Docker), orchestration (Kubernetes), and infrastructure provisioning (Terraform).
Experience with distributed systems, stream processing, and event-driven architecture.
Hands-on familiarity with benchmarking and performance profiling for storage systems, databases, and analytics engines.
Excellent communication skills-youll be expected to explain your thinking clearly, guide customer conversations, and collaborate across engineering and product teams.

This position is open to all candidates.

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8572794

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