לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER משרה מלאה

we are looking for a Senior Data Engineer.
Main responsibilities:
Provide the direction of our data architecture. Determine the right tools for the right jobs. We collaborate on the requirements and then you call the shots on what gets built.
Manage end-to-end execution of high-performance, large-scale data-driven projects, including design, implementation, and ongoing maintenance.
Optimize and monitor the team-related cloud costs.
Design and construct monitoring tools to ensure the efficiency and reliability of data processes.
Implement CI/CD for Data Workflows

Experienced Data Engineer? Excellent team player?
Come join a great team to overcome meaningful cyber challenges!
Our Data Solutions Group is looking for an exceptional Python developer with Data Engineering experience.

We're seeking an outstanding and passionate Data Platform Engineer to join our growing R&D team.

You will work in an energetic startup environment following Agile concepts and methodologies. Joining the company at this unique and exciting stage in our growth journey creates an exceptional opportunity to take part in shaping our data infrastructure at the forefront of Fintech and AI.

What you'll do:

Design, build, and maintain scalable data pipelines and ETL processes for our financial data platform.

Develop and optimize data infrastructure to support real-time analytics and reporting.

Implement data governance, security, and privacy controls to ensure data quality and compliance.

Create and maintain documentation for data platforms and processes.

Collaborate with data scientists and analysts to deliver actionable insights to our customers.

Troubleshoot and resolve data infrastructure issues efficiently.

Monitor system performance and implement optimizations.

Stay current with emerging technologies and implement innovative solutions.

Were looking for a highly skilled Senior Database Engineer to join our DBA team. In this role, youll design and optimize our large-scale database infrastructure while ensuring high availability, scalability, and performance. In your day-to-day, you will:
Design and optimize our large-scale database infrastructure to meet high availability and performance standards
Identify cost-effective areas for improvement in current databases
Collaborate with developers and software architects to model, create, and maintain robust data structures and the data layer
Lead and execute technical database-related POCs and benchmarks
Conduct regular audits of database design to ensure quality and compliance with service level agreements (SLAs)
Quickly identify and resolve critical production issues and provide on-call support as needed.

Required Data Engineer - ML & GenAI Platform
Job Description
As a data engineer in our data science group, youll build, use, and enhance our ML and GenAI platforms, powering data products and LLM-based services across. Youll design and operate data and MLOps infrastructure for batch inference, knowledge-base workflows, evaluation metrics, and fine-tuning pipelines. Collaborating with data scientists, product managers, and engineers, youll bring AI features into production at scale.
Extend and implement new capabilities in ML and GenAI platforms
Design and maintain scalable, reliable data architectures and pipelines for model training, LLM fine-tuning, inference, and evaluation
Develop and maintain Airflow DAGs for metrics calculation, batch inference, KB workflows, and other data science projects
Collaborate with data scientists and engineers to integrate models and GenAI features into production systems Ensure high-quality code through best practices in testing, code reviews, documentation, and CI/CD for data and ML workloads
Work with tools and platforms like Airflow, Spark, Docker, Python Serverless, Kafka, and multiple cloud environments to deliver scalable, cost-effective GenAI solutions.

we are looking for a Data engineer position - part of the iTero data team.
Key Responsibilities:
Collect and arrange data from various sources
Automate workflows and improve performance of existing data processes
Implement data quality checks, monitoring, and alerting to ensure accuracy and reliability
Optimize performance and costs of our data platform
Ensure compliance with data governance, security, and privacy standard

we are looking for a Senior Backend Developer.
What You'll Do:
Design and implement end-to-end features and services within a multi-service architecture.
Build and maintain a scalable data platform, incorporating advanced business logic and developing asynchronous, data-oriented, and scalable services.
Continuously improve and enhance the current data platform to ensure reliability, scalability, and performance.
Enhance and extend the functionality of existing systems.

It starts with you - an engineer who cares about building data pipelines and models that deliver reliable, trusted data. You value data quality, clean transformations, and making data accessible to those who need it. Youll work alongside experienced engineers to build ETL/ELT pipelines, maintain dimensional models, and implement quality checks that turn raw data into actionable intelligence.
If you want to grow your skills building data products for mission-critical AI, join mission - this role is for you.
:Responsibilities
Build and maintain ETL/ELT pipelines using platform tooling - workflows that extract from sources, apply transformations, and load into analytical stores.
Develop and maintain data models - fact/dimension tables, aggregations, and views that serve analytics and ML use cases.
Implement data quality checks - validation rules, tests, and monitoring for data freshness and accuracy.
Maintain documentation and lineage - keeping data catalogs current and helping consumers understand data sources and transformations.
Work with stakeholders to understand data requirements and implement requested data products.
Troubleshoot pipeline failures - investigating issues, fixing bugs, and improving reliability.
Write clean, tested, well-documented SQL and Python code.
Collaborate with Data Platform on tooling needs; work with Datastores on database requirements; partner with ML, Data Science, Analytics, Engineering, and Product teams on data needs.
Design retrieval-friendly data artifacts - RAG-supporting views, feature tables, and embedding pipelines - with attention to freshness and governance expectations.

It starts with you - a technical leader whos passionate about data pipelines, data modeling, and growing high-performing teams. You care about data quality, business logic correctness, and delivering trusted data products to analysts, data scientists, and AI systems. Youll lead the Data Engineering team in building ETL/ELT pipelines, dimensional models, and quality frameworks that turn raw data into actionable intelligence.
If you want to lead a team that delivers the data products powering mission-critical AI systems, join mission - this role is for you.
:Responsibilities
Lead and grow the Data Engineering team - hiring, mentoring, and developing engineers while fostering a culture of ownership and data quality.
Define the data modeling strategy - dimensional models, data marts, and semantic layers that serve analytics, reporting, and ML use cases.
Own ETL/ELT pipeline development using platform tooling - orchestrated workflows that extract from sources, apply business logic, and load into analytical stores.
Drive data quality as a first-class concern - validation frameworks, testing, anomaly detection, and SLAs for data freshness and accuracy.
Establish lineage and documentation practices - ensuring consumers understand data origins, transformations, and trustworthiness.
Partner with stakeholders to understand data requirements and translate them into well-designed data products.
Build and maintain data contracts with consumers - clear interfaces, versioning, and change management.
Collaborate with Data Platform to define requirements for new platform capabilities; work with Datastores on database needs; partner with ML, Data Science, Analytics, Engineering, and Product teams to deliver trusted data.
Design retrieval-friendly data products - RAG-ready paths, feature tables, and embedding pipelines - while maintaining freshness and governance SLAs.

It starts with you - an engineer driven to build modern, real-time data platforms that help teams move faster with trust. You care about great service, performance, and cost. Youll architect and ship a top-of-the-line open streaming data lake/lakehouse and data stack, turning massive threat signals into intuitive, self-serve data and fast retrieval for humans and AI agents - powering a unified foundation for AI-driven mission-critical workflows across cloud and on-prem.
If you want to make a meaningful impact, join mission and build best-in-class data systems that move the world forward - this role is for you.
:Responsibilities
Build self-serve platform surfaces (APIs, specs, CLI/UI) for streaming and batch pipelines with correctness, safe replay/backfills, and CDC.
Run the open data lake/lakehouse across cloud and on-prem; enable schema evolution and time travel; tune partitioning and compaction to balance latency, freshness, and cost.
Provide serving and storage across real-time OLAP, OLTP, document engines, and vector databases.
Own the data layer for AI - trusted datasets for training and inference, feature and embedding storage, RAG-ready collections, and foundational building blocks that accelerate AI development across the organization.
Enable AI-native capabilities - support agentic pipelines, self-tuning processes, and secure sandboxing for model experimentation and deployment.
Make catalog, lineage, observability, and governance first-class - with clear ownership, freshness SLAs, and access controls.
Improve performance and cost by tuning runtimes and I/O, profiling bottlenecks, planning capacity, and keeping spend predictable.
Ship paved-road tooling - shared libraries, templates, CI/CD, IaC, and runbooks - while collaborating across AI, ML, Data Science, Engineering, Product, and DevOps. Own architecture, documentation, and operations end-to-end.

As part of the Audiences team, youll work on highly scalable systems, tackle real-time challenges, and contribute to a platform that directly impacts the success of our customers campaigns.

Our team mixes disciplines from back-end, data, AI and front-end engineers and were looking for a great back-end data oriented developer that is passionate about what they do, who want to dive into the worlds of big data, microservices and production management at our scale, to help us reach our vision and goals

What youll do:
Solve diverse, complex problems at a large scale.
Collaborate with Product Managers, data scientists and Software Engineers to deliver innovative, user-facing products.
Independent - cradle to grave, own a feature from scratch to production.
Analyze and improve performance, scalability and stability of our products, environments and tools.
Continuously learn and evaluate new technologies in the everlasting effort to perfect our products and adapt to the ever-growing scale.

The Audiences team is responsible for building and maintaining our industry leading segmentation solution. Enabling customers to define, manage, and activate dynamic user segments across multiple advertising platforms.

We handle complex data pipelines, real-time audience updates, and seamless integrations with major media partners. Were also building predictive audience capabilities using AI to help our customers target the right users before they take action. Our work plays a critical role in driving user acquisition, engagement, and retention strategies for some of the worlds largest brands.

As part of the Audiences team, youll work on highly scalable systems, tackle real-time challenges, and contribute to a platform that directly impacts the success of our customers campaigns.

Our team mixes disciplines from back-end, data, AI and front-end engineers and were looking for a great back-end data oriented developer that is passionate about what they do, who want to dive into the worlds of big data, microservices and production management at our scale, to help us reach our vision and goals

What youll do
Solve diverse, complex problems at a large scale
Collaborate with Product Managers, data scientists and Software Engineers to deliver innovative, user-facing products.
Independent - cradle to grave, own a feature from scratch to production
Analyze and improve performance, scalability and stability of our products, environments and tools
Continuously learn and evaluate new technologies in the everlasting effort to perfect our products and adapt to the ever-growing scale

SQL & data Engineer | Direct employment from day one!
Join a successful, fast-growing Med-Tech startup making a real impact in the healthcare world!
Were looking for a hands-on SQL expert to own our data environment and fuel our growth. This is a unique opportunity to join a scaling success story while enjoying a flexible hybrid model with 3 days of working from home. WHAT YOULL DO
Work directly with messy, production SQL server data
Write and optimize complex SQL (CTEs, window functions, performance tuning)
Manage backups, reliability, and data integrity for SQL
Build Python pipelines to extract, clean, and transform data
Design and maintain MongoDB collections used for analytics and reporting
Support BI tools and internal reports with clean, reliable datasets
Partner closely with product and operations on real business questions.

DRS RADA is a leading defense high-tech company specializing in radar systems development. We are seeking an experienced Data Engineer to join our data engineering team. In this role, you will play a crucial part in designing, developing, and maintaining scalable data pipelines and infrastructure to support our AI department. This is an opportunity to work with cutting-edge technologies in a fast-paced production environment, driving impactful, data-driven solutions for the business. Key Responsibilities:
* Design, develop, and optimize ETL/ELT pipelines for large-scale data processing.
* Work with a modern data stack, including Databricks (Spark, SQL), Apache Airflow, and Azure services.
* Troubleshoot and optimize queries and jobs for performance improvements.
* Implement best practices for data governance, security, and monitoring.
* Stay updated with industry trends and emerging technologies in data engineering. If you're passionate about building scalable data solutions and thrive in a fast-paced environment, we’d love to hear from you!

We are looking for a Senior Data Engineer to join our Platform group in the Data Infrastructure team.
Youll work hands-on to design and deliver data pipelines, distributed storage, and streaming services that keep our data platform performant and reliable. As a senior individual contributor you will lead complex projects within the team, raise the bar on engineering best-practices, and mentor mid-level engineers - while collaborating closely with product, DevOps and analytics stakeholders.
About the Platform group
The Platform Group accelerates our productivity by providing developers with tools, frameworks, and infrastructure services. We design, build, and maintain critical production systems, ensuring our platform can scale reliably. We also introduce new engineering capabilities to enhance our development process. As part of this group, youll help shape the technical foundation that supports our entire engineering team.
Code & ship production-grade services, pipelines and data models that meet performance, reliability and security goals
Lead design and delivery of team-level projects - from RFC through rollout and operational hand-off
Improve system observability, testing and incident response processes for the data stack
Partner with Staff Engineers and Tech Leads on architecture reviews and platform-wide standards
Mentor junior and mid-level engineers, fostering a culture of quality, ownership and continuous improvement
Stay current with evolving data-engineering tools and bring pragmatic innovations into the team.