דרושים » דאטה » data tech lead (Azure)

We are looking for a highly skilled Data Engineer . to build and maintain robust, scalable data pipelines and data marts acting as the connective tissue for intelligence insights generation that serves executive stakeholders , internal customers and 3rd party
The Fintech AI & Data group is looking for a staff Data Engineer to work closely with analysts, data scientists, and software developers and strengthen Fintech by building data capabilities and AI transformation.
Responsibilities:
Gather data needs from internal customers like product and analysts, and translate those requirements into a working database and analytic software.
Design, build, and maintain scalable, reliable batch and real time data pipelines, data marts and warehouse supporting executive dashboards, operational analytics, and internal customer use cases
Ensure high data quality, observability, reliability, and governance across all data assets
Optimize data models for performance, cost-efficiency, and scalability
Develop data-centric software using leading-edge big data technologies.
Build data capabilities that enable automated agentic insights and decision intelligence
Develop reusable data services and APIs that power AI-driven workflows
Evolve our data architecture into an AI-native data layer designed to power LLMs, AI agents, and intelligent applications
Collaborate with analytics, product, and AI teams to translate business needs into scalable data solutions
Influence the software architecture and working procedures for building data and analytics
Work bBe the go-to person for anything and everything regarding understanding the data - exploration, pipelines, analytics, etc. and work both independently and as part of a team
How youll succeed
Have an impact on satisfying customers and reducing financial fraud
Help build the team by hiring the best talent
Contribute toexperiments and research on how to enhance our capabilities
Learn new technologies and methodologies
Collaborate with other data engineers, analysts, data scientists and developers
Be proactive with a self-starter attitude
Be a good listener, while also having strong opinions on what is right
Be fun to be around :)

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!

Were looking for a highly skilled and motivated Senior Data Engineer to join the Resolve (formerly DevOcean) team at our company. In this role, youll be responsible for designing, building, and optimizing the data infrastructure that powers our SaaS platform. Youll play a key role in shaping a cost-efficient and scalable data architecture while building robust data pipelines that serve analytics, search, and reporting needs across the organization.
Youll work closely with our backend, product, and analytics teams to ensure our data layer remains fast, reliable, and future-proof. This is an opportunity to influence the evolution of our data strategy and help scale a cybersecurity platform that processes millions of findings across complex customer environments.
Roles and Responsibilities:
Design, implement, and maintain data pipelines to support ingestion, transformation, and analytics workloads.
Collaborate with engineers to optimize MongoDB data models and identify opportunities for offloading workloads to analytical stores (ClickHouse, DuckDB, etc.).
Build scalable ETL/ELT workflows to consolidate and enrich data from multiple sources.
Develop data services and APIs that enable efficient querying and aggregation across large multi-tenant datasets.
Partner with backend and product teams to define data retention, indexing, and partitioning strategies to reduce cost and improve performance.
Ensure data quality, consistency, and observability through validation, monitoring, and automated testing.
Contribute to architectural discussions and help define the long-term data platform vision.

Required 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.
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.
End-to-end ownership mindset with a proactive, production-first approach.

We are looking for a motivated Data Engineer to join our growing Data team. This is an exciting opportunity to be part of a core group responsible for building, maintaining, and scaling our data platform, while working closely with Product, Engineering, and business teams.

You will play a key role in developing reliable data pipelines, ensuring data quality and consistency, and enabling data-driven decision-making across the organization.

Responsibilities:
Design, build, and maintain data pipelines and data models to support analytics and reporting needs.
Work with structured data across databases, data lakes, and data warehouses.
Write efficient and maintainable SQL and Python code for data transformation and validation.
Ensure data quality, consistency, and basic data lineage across systems.
Collaborate with Product, Engineering, and business stakeholders to understand data requirements.
Support dashboards and reporting tools by providing clean, well-modeled data.
Contribute to improving data standards, documentation, and best practices.

Responsibilities
Design, build, and maintain scalable ETL/ELT pipelines to integrate data from diverse sources, optimizing for performance and cost efficiency.
Leverage Databricks and other modern data platforms to manage, transform, and process data
Collaborate with software teams to understand data needs and ensure data solutions meet business requirements.
Optimize data processing workflows for performance and scalability.

Were looking for a senior‑level Data Platform Solutions Engineer who is both data‑savvy and customer‑focused. In this role youll help our customers run large‑scale data and AI workloads, tackling technical challenges across modern data environments. Youll blend deep troubleshooting expertise with tool‑building and solution design, while partnering closely with our teams and customers to ensure successful deployment and operation of our data‑platform offerings-both on‑premises and SaaS.
You will:
Assist customers with complex data‑lake and AI workloads on our data platform.
Diagnose and remediate high‑severity, multi‑layer issues spanning infrastructure, Kubernetes, data engines, storage, and networking.
Create and refine tools, automation, and solutions that boost environment stability and operational efficiency.
Deliver architectural guidance and configuration best practices to enhance performance, scalability, and resiliency.
Serve as the technical liaison among Customer Support, Product Management, and R&D, turning customer insights into product enhancements.
Take the first step towards your dream career
Job ID:R285903.

Required Senior Data Engineer
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.
Develop and manage orchestration tools, governance tools, data discovery tools, and more.
Work with other team members of the engineering group, including data scientists, data architects, and data analysts, to provide solutions using a use case-based approach that drives the construction of technical data flows.

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.