לוח משרות דרושים הייטק דאטה

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 seeking an experienced Data Team Lead to build, lead, and scale our data function. This is a hands-on leadership role that combines strategic thinking, technical excellence, and people management. You will build and manage a team of Data Engineers and Data Analysts, while working closely with senior management and cross-functional leaders to translate data into measurable business impact.
This role is ideal for someone who thrives in a fast-paced startup environment, enjoys influencing decision-making at the highest levels, and is passionate about embedding a data-driven mindset across the organization.
What You'll Do:
Lead and mentor the Data team, and support their professional growth while achieving impact goals of the marketing data structure such as: multi touch attribution model, creative analytics and automated data governance processes.
Define and own the data vision, roadmap, infrastructure, and best practices aligned with company objectives.
Act as a trusted data partner to executive leadership and senior stakeholders, influencing strategy through insights and analysis while promoting a strong data-driven culture.
Oversee the design, build, and maintenance of a scalable and reliable data warehouse.
Lead the design, implementation, and optimization of ETL/ELT pipelines to integrate data from multiple internal and external sources.
Ensure high standards for data quality, governance, integrity, and documentation.
Translate complex datasets into clear, actionable insights that support the different departments' needs and the company growth through operational excellence.
Support advanced analytics use cases including forecasting, experimentation (A/B testing), and performance measurement.
Review and elevate dashboards, reports, and analyses to ensure clarity, accuracy, and executive relevance.
Identify gaps in data collection and proactively propose solutions to improve visibility and decision-making.

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.

Were looking for an experienced Data & BI Manager to lead and shape our data domain as part of our IT Applications group.

We are embarking on a major data transformation journey, centered around the implementation of Microsoft Fabric end-to-end. This is not a maintenance role - its a build, lead, and scale opportunity.

You will play a critical role in defining our data vision, driving architecture decisions, leading a large-scale BI transformation, and gradually building and managing an internal Data & BI team. This role sits at the intersection of technology, business, and leadership, with direct impact on decision-making across the organization.

Your mission:

Leadership & Ownership:
Own and lead the Data & BI domain within IT Applications.
Lead and professionally manage the Data & BI team (team build-up over time).
Take a central role in the organization-wide transformation to Microsoft Fabric.

Strategy, Architecture & Innovation:
Define the long-term Data & BI strategy, including technologies, platforms, and methodologies (e.g. Data Governance, Data Mesh).
Design, build, and maintain the companys data architecture:
Data Warehouse, Data Lake, Data Marts, ETL/ELT pipelines.
Lead the adoption of advanced analytics capabilities, including AI / GenAI, to generate insights and optimize business processes.
Enable self-service BI by implementing tools and best practices that empower analysts and business users.

Delivery & Business Partnership:
Lead the full lifecycle of Data & BI solutions - from requirements gathering to production.
Own data quality, data integrity, and information security across all data layers.
Work closely with senior management and business leaders to understand needs, translate them into technical solutions, and clearly communicate insights and outcomes.

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.

We are looking for a Data Operations Team Lead to lead and scale our data operations function. This role sits at the intersection of data, algorithms, and operations, and is critical to the success of our computer vision and AI models.
You will lead a distributed team responsible for data collection, annotation, quality control, and delivery, while working closely with Algorithm teams to understand model needs, prioritize requests, and ensure reliable, high-quality data pipelines.
This is a hands-on leadership role - you will manage people and processes, but also actively design, build, and improve data workflows.
About The Role
Lead and manage the Data Operations team, including annotation teams in Israel and a large remote team in India
Serve as the primary interface between Data Operations and Algorithm teams: understand model requirements, prioritize tasks, and plan data delivery
Own end-to-end data workflows, from model improvement needs through data definition, annotation guidelines, execution, and delivery
Ensure high data quality through close monitoring, validation, troubleshooting, and root-cause analysis
Design and maintain clear annotation guidelines, documentation, and training materials
Closely manage remote annotation teams, including weekly syncs, hands-on oversight, and deadline management
Own and operate the annotation pipeline using industry tools (e.g., CVAT)
Monitor progress, track performance, and continuously improve efficiency and quality
Own annotation budgets, monthly reporting, and validation of hours and outputs
Evaluate, benchmark, and implement new tools and processes in the data and annotation domain
Work hands-on with scripts, AI tools, and monitoring systems as needed to support data quality and operations.

We are on a mission to enable enterprises to adopt AI safely and securely. Our approach combines advanced AI research with practical implementation to offer seamless integration and protection for our clients' AI based tools and infrastructure.
We are looking for a Senior Data Scientist / Applied AI Researcher with deep expertise in NLP and LLM-based systems, and the ability to operate across the full lifecycle, from problem formulation and research design to production deployment and real-world iteration.
You wont be working on isolated experiments. Youll be part of a multidisciplinary team that owns the system end-to-end and is responsible for how it behaves under real production traffic.
This role requires strong scientific discipline and the maturity to balance innovation with practical constraints.
What youll do
End-to-End Ownership: Lead AI security solutions from problem formulation and research design through model development, evaluation, and production deployment. Ensure solutions are measurable, reliable, and effective under real-world traffic.
Drive Technical Direction: Take responsibility for ambiguous AI security problems, propose thoughtful approaches, and drive structured experimentation and deep model analysis.
Build for Scale: Design systems that are not only accurate, but scalable, efficient, and robust.
Staying Updated: Continuously explore advances in NLP and LLM-based systems, and critically assess what is worth integrating into a production environment.

At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Conduct hands-on research and development of cutting-edge models
Take research projects from ideation to deployment and production
Work closely with domain experts and the engineering department to improve and create new innovative solutions.
Help define the AI product roadmap.

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.

At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Conduct hands-on research and development of state-of-the-art models, algorithms, and systems.
Lead research projects end-to-end from problem formulation, ideation, and experimental design to prototyping and transition into production.
Explore new methodologies and develop creative approaches to solve complex challenges.
Identify ambitious research directions and invent novel approaches to solve complex, high-impact problems.
Shape the research roadmap and influence long-term technical strategy across the organization.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company'sAI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Conduct cutting-edge research in natural language processing and large language models.
Design, train, and optimize large-scale neural network models for advanced applications.
Transition research projects from ideation through deployment and scaling.
Collaborate closely with cross-functional teams, including domain experts, product managers, and engineers, to deliver impactful AI solutions.
Define and contribute to the AI and NLP product roadmap.

Were looking for a Senior Data Scientist who will join our growing Detection group. You'll be a significant part of the development of our state-of-the-art anomaly detection models to find and protect against nation-sponsored cyber-attacks. In this role, you will work with product, engineering, and cyber teams to train, evaluate, and deploy anomaly detection models on a massive scale.
The Responsibilities
Analyze, transform and clean large, complex data sets from various sources to ensure data quality and integrity for analysis.
Conduct hands-on research and development of state-of-the-art models and algorithms.
Extract relevant features from structured and unstructured data sources, design and engineer new features and feature selection methodologies to enhance model performance.
Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics.
Lead research projects end-to-end from problem formulation, ideation, and experimental design to prototyping and transition into production.
Explore new methodologies and develop creative approaches to solve complex challenges.

Required Data Engineer II - GenAI
20718
Leadership/Team Quote:
This opening is for the Content Intelligence team within the Marketplace AI department.
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
As a Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

Required Senior Data Engineer I - GenAI Foundation Models
21679
Leadership/Team Quote:
This opening is for the Content Intelligence team within the Marketplace AI department.
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.