לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER

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.

We are seeking a seasoned and execution driven VP, head of data platform to lead all the R&D tracks of the Data and Analytics organization in our company. This role focuses on leading a complex data engineering organization at scale, driving delivery, operational excellence and cross-company enablement through world-class data platforms and tools.
This leader will serve as the engineering owner of our data platform, managing multiple data infra, data engineering and BI development teams, overseeing extensive resources, and ensuring the delivery of high-quality, scalable, and reliable data products and services. This position requires a strong technical background combined with exceptional leadership, strategic thinking, and cross-functional collaboration skills.
He will also act as a key stakeholder in defining the architecture and strategic direction of our data infrastructure, pipelines, AI/ML infra and platforms to support the company's rapid growth and evolving business needs.
Hybrid
Full-time
What youll do: 
Lead and manage the entire data platform, including:
Real-Time Data & Streaming Infrastructure: Introduce and engineer robust data streaming infrastructures (e.g., using Kafka, Pub/Sub, Dataflow) to enable near-real-time data ingestion and scalable low-latency data serving, unlocking advanced analytics and critical use cases.
Data engineering teams responsible for the data ingestion, transformation and delivery pipelines
BI infra and development teams owning the cross-company consumption layer, including BI tools, BI data layers and dashboards
Serve as the operational and delivery lead across the data platform, ensuring strong project execution, roadmap alignment and measurable business impact
Data Engineering & Architecture Oversight: Lead the design, development, and evolution of scalable data platforms, encompassing data lakes, data warehouses, and advanced data products, ensuring they meet performance, reliability, and business requirements.
Operational Excellence & Reliability: Establish and drive engineering operational excellence processes across data engineering, significantly improving data quality, availability, and system reliability. Implement frameworks for proactive monitoring, alerting, and incident management, reducing major incidents and ensuring continuous visibility into data flows.
Advanced Data Observability: Integrate and leverage cutting-edge data observability solutions (e.g., Monte Carlo) to provide comprehensive visibility into data pipelines, enabling proactive detection and resolution of anomalies.
Cross-functional Collaboration & Stakeholder Management: Collaborate extensively with product, analytics, business, and infrastructure teams to align data strategies with overarching business priorities, ensuring the delivery of high-quality data products that meet diverse user needs.
Innovation & Technology Adoption: Stay abreast of the latest data, cloud, and AI trends, driving the evaluation and adoption of modern cloud-native technologies to continuously improve platform capabilities and future-proof the ecosystem.
Leadership & Team Growth: Lead, mentor, and grow a large team of data engineers, fostering a culture of technical excellence, continuous learning, and agile methodologies. Oversee budget management and drive talent development within the team.
Data Governance & Quality: Oversee the implementation of standards for data quality, data integrity tools, governance, privacy, and regulatory compliance across the data ecosystem.

As a Data Engineer on the IT production team in our TLV Office, youll play a vital role impacting billions of users, work with petabytes of data in extreme scale and make a difference, send us your resume. Or In other words, If you like: Database performance tuning, Doing it at scale, Building tools that will help you do it Using AI to make it legendary our company is the place for you.
How youll make an impact as a data engineer
Advise on the optimal database design by analyzing application behavior and business requirements
Design data flow processes
Work with AI at scale on developing high impact solutions
Proactively monitor and optimize database queries, processes, tables and resources
Initiate and lead cross-group optimization processes
Write utilities and design dashboards that will help us maintain, monitor and optimize the company production database environment and data pipeline
Develop automation tools for large cluster maintenance
Face challenges such as scale, visibility and automation
Be involved in both development and infrastructure projects.

Required Senior Data Engineer
Description
Join our core platform engineering team, developing our AI-powered automotive data management platform.
We are developing the next generation data-driven products for the Automotive industry, focusing on cybersecurity (XDR) and vehicle quality. Our products monitor and secure millions of vehicles worldwide and help automakers leverage connected vehicle data to deliver cyber resilience, safety, customer satisfaction and increase brand loyalty.
Our Data Engineering & Data Science Group leads the development of our Iceberg-based data platform, including data lake, query engine, and ML-Ops tools, serving as a solid AI-ready foundation for all our products.
At the core of our Engineering Team, you will build and operate scalable, production-grade customer-facing data and ML platform components, focusing on reliability and performance.
Technological background and focus: Iceberg, Trino, Prefect, GitHub Actions, Kubernetes, JupyterHub, MLflow, dbt
This role is full-time and is Herzliya, Israel based.
Responsibilities
Design, build, and maintain scalable data pipelines to ingest and transform batch data on our data lake, enabling analytics and ML with strong data quality, governance, observability, and CI/CD.
Build and expand our foundational data infrastructure, including our data lake, analytics engine, and batch processing frameworks.
Create robust infrastructure to enable automated pipelines that will ingest and process data into our analytical platforms, leveraging open-source, cloud-agnostic frameworks and toolsets.
Develop and maintain our data lake layouts and architectures for efficient data access and advanced analytics.
Build our ML platform and automate the ML lifecycle.
Drive business-wide ML projects from an engineering perspective.
Develop and manage orchestration tools, governance tools, data discovery tools, and more.
Work with other team members of the engineering group, including data architects, data analysts, and data scientists, to provide solutions using a use case-based approach that drives the construction of technical data flows.

As a Senior Algo Data Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Senior Algo Data Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

As a Staff Algo Data Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
As a Staff Algo Data Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet
Our tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.