לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER

We are looking for a highly enthusiastic Data Engineer to join our group on the journey of leveraging Big Data to revolutionize our offering, business operations and decision making across the companys ecosystem.


Job Responsibilities:

Design, build & deploy backend data solutions to prod, starting from research and design to development and testing.
Work closely with data engineers, product, architects and other R&D teams to deliver the best solutions to the business.
Monitor the solutions in production to make sure they are fully stable, scalable and performant at all times.
Work closely with data sciences experts

We are looking for a Data Engineer to join our growing team!
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.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
In this role, you will be responsible for:
Designing, building, and maintaining scalable data pipeline architectures
Developing ETL processes to integrate data from multiple sources
Creating and optimizing data models for efficient storage and retrieval
Implementing data quality controls and monitoring systems
Collaborating with data scientists and analysts to deliver data solutions
Building and maintaining data warehouses and data lakes
Performing in-depth data analysis and providing insights to stakeholders
Taking full ownership of data quality, documentation, and governance processes
Building and maintaining comprehensive reports and dashboards
Ensuring data security and regulatory compliance

Responsibilities:
Design and maintain scalable data pipelines with Spark Structured Streaming.
Implement Lakehouse architecture with Apache Iceberg.
Develop ETL processes for data transformation.
Ensure data integrity, quality, and governance.
Collaborate with stakeholders and IT teams for seamless solution integration.
Optimize data processing workflows and performance.

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.

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.

M:AD Growth is looking for an experienced Delivery Leader to head our analytics and data engineering team. You will be responsible for the end-to-end execution of complex data projects, ensuring technical excellence and driving measurable impact for our enterprise clients. This role is ideal for a leader with a strong background in Digital or Product Analytics, experienced in measuring and optimizing user behavior across large-scale digital products and ecommerce platforms. This role is ideal for a builder-manager who can translate high-level strategy into high-performance data operations while leading, mentoring, and developing a team of analysts and data engineers.

Responsibilities:

* Lead and develop a multidisciplinary data team. Manage and grow a team of Analysts Data Engineers and while driving advanced AI methodologies and analytical standards.
* Measure and optimize digital user journeys across enterprise websites, applications, and ecommerce platforms. Define tracking strategies and analytical frameworks for key digital processes such as acquisition flows, onboarding journeys, service requests, and ecommerce funnels.
* Drive data-driven optimization by identifying performance gaps, user friction points, and growth opportunities through behavioral data and funnel analysis.
* Own the full analytics lifecycle, from building robust data foundations and tracking architectures to delivering dashboards, deep analyses, predictive models, and automated insights.

* Define and enforce analytics architecture standards for GA4 tracking, BigQuery data modeling, and Looker Studio reporting.

We are looking for an Analytics Engineer to join Orcas next-generation big data platform. In this role, you will play a significant part in implementing algorithms and AI-driven logic into our product, helping notify customers about ocean dangers and making maritime voyages safer worldwide.

You will play a central role in building the semantic tables and business logic layer that power advanced product capabilities, real-time notifications, and data-driven decision-making across our platform. Working closely with the Data Science team, you will define high-impact features for their models and integrate algorithms directly into the semantic layer.

This is a temporary position (Maternity leave replacement)

What Youll Do

Design and implement business logic and semantic tables that serve as the foundation for advanced platform features.
Build robust, scalable services that generate real-time notifications for hundreds of ships and fleet managers worldwide.
Deliver high-quality data products that serve operational systems, algorithms, and human-facing applications.
Quickly learn Orcas maritime domain and turn complex data into reliable semantic tables that power product features
Collaborate closely with data scientists, product teams, and engineers to embed algorithms and AI capabilities into production systems.
Be a pivotal contributor in a highly professional, impact-driven data team.

Were looking for a Senior Data Architect to help shape how high-growth startups build and scale on AWS. In this role, youll design and deliver end-to-end data and analytics solutions - from architecture and pipelines to visualization and insights - guiding customers from concept through production. Youll work closely with startup founders, technical leaders, and account executives to create scalable, cost-efficient architectures that drive real business impact.
📍 Work location - hybrid from Tel Aviv
If you are interested in this opportunity, please submit your CV in English.
Responsibilities:
Design, develop, and implement data & analytics solutions to meet business requirements and create cost-efficient, highly available, and scalable customer solutions, including Well-Architected reviews and SoW.
Research and analyze current solutions and initiate improvement plans.
Collaborate with other engineers and stakeholders to ensure solutions are designed and developed according to best practices.
Lead workshops, POCs, and architecture reviews with startup customers, conferences, webinars, and more.
Stay up to date on Data Engineering and Analytics trends and contribute to internal enablement.
Frequent travels - locally (on-demand to meet with customers and partners and attend local events) and abroad (at least once a quarter).

We are looking for an Experienced Big Data Engineer who loves solving complex problems at an extreme scale. In this role, you arent just building "internal pipelines"-you are developing the actual product our clients interact with. You will write high-performance code, optimize your own Spark processes for client freshness, and own features end-to-end. We need a "problem solver by nature, optimizer in their soul" who brings both technical depth and a great personality to a high-speed, deep technical team.

What youll do
Build Client-Facing Features: Design and implement high-scale product features for premium clients - from architecture to production deployment.
Performance Engineering: Optimize scalable data pipelines and distributed processes to meet strict client SLAs. Every millisecond of freshness matters.
System Integrity: Ensure uncompromising data accuracy and performance across massive, complex datasets.
Strategic Collaboration: Partner with upstream data providers, client-side teams, and Product Managers to turn raw events into production-grade features.

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're looking for a Data Engineer with 4+ year experience to join our Data Engineering team and help us build and scale our production-grade data platform. You'll work on high-performance systems built on self-hosted ClickHouse, optimize complex data pipelines, and collaborate closely with Product, Analytics, and Infrastructure teams to deliver reliable, fast, and scalable data solutions.

This is a hands-on technical role where you'll have a significant impact on how we ingest, model, store, and serve data that powers our analytics and AI-driven products.
Youll play a key role in shaping the direction of our data platform and have meaningful ownership over critical components of our architecture.

What You'll Do:
Data Modeling & Architecture
Design and evolve data models that reflect business logic and support analytical use cases
Collaborate with the BI and Analytics teams to understand data requirements and translate them into efficient schemas
Performance Optimization
Optimize ClickHouse schemas, partitioning strategies, indexing, and compression
Profile and tune slow queries to improve performance and reduce costs
Implement systems that ensure data quality, consistency, and operational efficiency (e.g., deduplication, validation, anomaly detection)
Monitor pipeline health, data freshness, and query performance with appropriate alerting mechanisms
SQL Compiler Development
Develop and maintain the SQL Compiler layer that translates high-level queries into optimized ClickHouse execution plansImplement query optimization and rewriting strategies to improve performanceDebug and resolve compiler issues to ensure accurate and efficient query translation

Data Pipeline Development & Collaboration
Review and advise the Integration team on pipeline architecture, performance, and best practices.
Provide guidance on data modeling, schema design, and optimization for new data sources.
Troubleshoot and maintain existing pipelines when issues arise or optimization is needed
Ensure data freshness, reliability, and quality across all ingestion pipelines.
Collaboration & Support
Work closely with the Integration team to ensure smooth data ingestion from new sources.
Partner with Infrastructure to support high availability and disaster recovery
Support other teams across the company in accessing and using data effectively.

We are looking for an Experienced Data Engineer to join our marketing team and take end-to-end ownership of our data platform and production data pipelines. In this role, you will be responsible for building robust, scalable, and observable data systems that power analytics, reporting, and downstream business use cases. You will work deeply hands-on with data infrastructure, modeling, and orchestration, and act as a key technical partner to Marketing, Sales Product and Business and Finance teams.
This role suits someone who enjoys working close to the metal, designing systems that scale, and solving ambiguous data problems in a dynamic startup environment. You will play a critical role in shaping how data flows through the company, setting engineering standards, and ensuring data is trustworthy, performant, and ready for growth.
What You'll Do:
Design, build, and maintain scalable, reliable data pipelines and data warehouse architectures to support analytics and business intelligence needs.
Own the end-to-end ETL/ELT processes - ingesting data from internal and external sources, transforming it, and making it analytics-ready.
Model and optimize data structures (fact tables, dimensions, semantic layers) to support performant querying and reporting.
Ensure high standards of data quality, integrity, observability, and reliability across all data assets.
Partner closely with Analytics, Product, Marketing, and Finance teams to understand data requirements and deliver robust data solutions.
Implement monitoring, alerting, and testing frameworks to proactively identify data issues.
Optimize warehouse performance and cost efficiency (query optimization, partitioning, clustering, etc.).
Identify gaps in data collection and work with engineering teams to improve instrumentation and data availability.
Support experimentation and analytics use cases by enabling clean, trustworthy datasets for A/B testing and analysis.
Document data models, pipelines, and best practices to support scale and knowledge sharing.

Youll work in an awesome environment alongside some of the most innovative people in the industry, using cutting-edge technologies and tools (video editing, Gen AI, data, etc.). At our company, you have the opportunity to directly influence the products and tools used by our clients, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN - and thats just the beginning of what our company has to offer! Join us and be a part of the best team in tech as we Fuel the Fandom worldwide.
What youll do:
Design and develop scalable, efficient services, APIs, and automations as founder of this area
Build data pipelines, ETL processes, and integrations that power products and internal tools
Own features end-to-end: design, implementation, CI/CD, monitoring, and observability
Develop and optimize data models, ensuring high-performance data infrastructure
Build and schedule workflows with python orchestrator and integrate with data platforms
Optimize performance, reliability, and security across services
Write high-quality, maintainable code in a rich data environment
Collaborate with Product, R&D, Operations, and Business to deliver impactful data-driven solutions
Work with SAAS environments and containerized deployments.

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 our companys mission and build best-in-class data systems that move the world forward - this role is for you.
The 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.