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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 seeking a Senior Data Scientist to be one of the first data science hires for our newly formed ML team. This is a unique ground-floor opportunity to build our data science capabilities from scratch and have direct influence on our analytical and modeling approaches. This role combines advanced data science expertise with foundational contributions, requiring someone who can develop sophisticated models, conduct deep analytical research, and help establish the data science methodologies that will guide the team as we scale. As one of our founding data scientists, you'll work closely with our Tech Lead to shape our modeling approaches, define our analytical standards, and build the fundamental data science skill set for future hires.
What You'll Do:Empty heading
Build foundational data science capabilities: As one of our first data science hires, work with the Tech Lead to develop core modeling methodologies, analytical frameworks, and research practices
End-to-end model development: Take ownership of complete ML model lifecycle - from initial research and experimentation through production deployment and monitoring
Build impactful models: Design, develop, and deploy machine learning models that solve complex business problems across payments, risk, and customer analytics
Define analytical standards: Help establish best practices for data exploration, feature engineering, model validation, and statistical analysis
Conduct deep research: Lead exploratory data analysis and research initiatives to uncover insights and identify ML opportunities across the business
Partner with stakeholders: Work closely with business teams to understand requirements, translate problems into data science solutions, and communicate findings effectively
Establish model development practices: Help set up our approach to model experimentation, A/B testing, and performance monitoring
Shape data science culture: Contribute to establishing the team's analytical rigor, documentation standards, and knowledge-sharing practices
Drive innovation: Research and evaluate new ML techniques, algorithms, and approaches that could benefit our business use cases.

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 Senior Data Scientist to drive the development and implementation of AI-based solutions that solve complex business challenges across our innovative SaaS platform. In this key role, youll work cross-functionally to lead end-to-end AI projects-from data exploration to deployment-helping shape the future of our intelligent products and user experiences.
If youre passionate about machine learning, LLMs, and real-world impact, and thrive in a collaborative, high-velocity environment, wed love to connect.
What You Will Do:
Identify AI opportunities to enhance product experiences and operational efficiency.
Collect, analyze, and model diverse financial datasets to develop actionable AI Products.
Own the full AI solution lifecycle-from problem definition to research, modeling, and hands-on implementation.
Break down complex problems into well-defined, structured work plans.
Collaborate closely with developers, product managers, and other stakeholders to integrate AI solutions seamlessly into products.
Stay up to date with AI, ML, and LLM trends, translating them into practical applications.
Provide technical leadership and mentorship to junior data scientists while balancing immediate delivery with long-term innovation.

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.

Required Head Of Tech Data
Come and be you with us
Being a Bobber is all about being you. We want you to bring all parts of yourself to work, giving you the freedom and confidence to be the best you and do your best work. If thats bubbly, shy, precise, funny, bold, kind, honest, brilliant, or anything in between, were waiting
with open arms. Come join us.
About you:
As our Head of Tech Data, you will be a senior member of the Tech Leadership team, responsible for defining and driving our Tech Data strategy across the organization.
This is a foundational leadership role. You will shape how data is consumed across our technology organization, from principles and operating model to tooling, metrics, and ways of working. You will assess our current state, identify the most meaningful gaps and risks, and define where data can create the greatest impact for our teams and products.
You will operate comfortably at both the strategic and execution levels, influencing leadership decisions, aligning senior stakeholders, and getting hands on when needed. You will lead the creation of standards, frameworks, and best practices that scale and have lasting impact, while working closely with Product, Design, Engineering, and the broader Data organization.
Lead and develop the Product Analytics team within Tech.
Define and own the Tech Data strategy, shaping how data supports decision making across the organization.
Act as the strategic and technical authority for Tech Data, assessing current practices and setting the operating model, infrastructure, standards, and roadmap.
Establish clear ownership and governance to ensure consistency, quality, and trust.
Partner closely with Engineering, Product, Design, and Data to embed data into every stage of the development lifecycle.
Drive innovation in Tech Data, including the use of AI to enable speed & scale.
Establish Tech Data metrics and reporting that give leadership visibility and support clear, actionable decisions.
Own the lifecycle of data products, from discovery and modeling through KPI definition, adoption, and maintenance.
Shape and lead company KPIs, ensuring consistency across dashboards & AI outputs.
Ensure data products are trusted, scalable & used to drive measurab

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.

We are looking for an experienced Senior Data Scientist to join our rapidly growing data science team, focusing on creating ML-driven prediction and anomaly detection models. As a Senior Data Scientist, you will lead the analysis of large (often massive) datasets, develop models and algorithms to meet customer needs. You will be working closely with other data scientists, data engineers, product managers and domain experts to improve our automotive purpose-built data management platform, focusing on vehicle quality, cybersecurity and API security use cases.
As a Senior Data Scientist, youll play a pivotal role in driving innovation and shaping the future of ML-based solutions in automotive quality and cyber security. Youll work on challenging datasets, develop advanced models, and see your work integrated into impactful, real-world applications.
Your work will directly enhance the safety and quality of advanced automotive systems and cybersecurity solutions. We prioritize talent development, offering you opportunities to learn, innovate, and grow in a collaborative environment.
This role is full-time and is Herzliya, Israel based.
Responsibilities
Conduct in-depth research on large and diverse automotive live streaming tabular datasets, preprocess the data, as well as extract and present key insights
Search and craft indicative features that will enhance the value of ML models
Explore, design and deploy cutting-edge ML models or algorithms solutions for prediction purposes and anomaly detection
Collaborate closely with domain experts and peers to research and implement models and algorithm flows that best fit requirements
Partner with our data engineering and development teams to devise innovative solutions for productization
Encourage collaboration and knowledge-sharing within the data science team.

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 Senior Data Scientist, youll play a vital role in turning algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
How youll make an impact:
As a Senior Data Scientist, youll bring value by:
Be responsible for the entire algorithmic lifecycle in the company: data analytics, prototyping of new ideas, implementing algorithms models in a production environment and then monitoring and maintaining them
Turn algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
Work on a daily basis with some of the hottest trends in todays job market: machine/deep learning, big data analytics/engineering and cloud computing
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems
Influence directly on the way billions of people discover the internet
Work on projects such as Internet Personalization, Content Feed, Real Time Bidding, Video Recommendations and much more.

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.