דרושים » דאטה » Data Center Engineer, HPC and AI

We are looking for a Senior Data Engineer to join the NSV (Network Solutions Validation) group. NSV builds high-performing software automation for our Data Center environments and helps drive the data growth of the world's biggest companies. In this role, you will design, build, and maintain scalable, high-performance data pipelines that handle massive volumes of data from hardware, communication modules, firmware, and large-scale AI and HPC clusters. You'll also contribute to our growing Agentic AI initiatives, helping develop AI Agents that bring our data capabilities to the next level.
What you'll be doing:
Define and execute the group's data technical roadmap, aligning with Infra, DevOps, and Performance teams
Design and maintain flexible ETL/ELT frameworks for ingesting, transforming, and classifying cluster verification and telemetry data
Build and optimize streaming pipelines using Apache Spark, Kafka, and Databricks, ensuring high throughput, reliability, and adaptability to evolving data schemas
Ensure data quality and pipeline health through observability standards, schema validation, lineage tracking, monitoring, and alerting
Deliver reliable insights for cluster performance analysis, telemetry visibility, and end-to-end test coverage
Support self-service analytics for engineers and researchers via Databricks notebooks, APIs, and datasets
Drive best practices in data modeling, code quality, and operational excellence; collaborate with cross-functional teams to support data-driven decision-making
Contribute to the development of AI Agents that enhance the visibility and accessibility of insights and data for our users.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

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.
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.

We are looking for a strong, hands-on Data Engineer to join our team and play a key role in building our data infrastructure from the ground up. In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases. You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption. This is a great opportunity for an executor who enjoys building, moving fast, and making an impact.
What will your job look like?
Design, build, and maintain robust and scalable data pipelines (batch and real-time) end-to-end.
Design and implement scalable, flexible data architectures to support evolving business needs.
Build and manage data platforms, including data lakes and data warehouses.
Integrate multiple data sources (structured and unstructured) into a unified data platform using batch (ETL) and real-time streaming solutions.
Design and implement efficient data models, schemas, and database structures (SQL / NoSQL).
Develop and implement data quality processes to ensure accuracy, consistency, and reliability.
Monitor, optimize, and troubleshoot data infrastructure to meet performance and SLA requirements.

Were looking for a Data Engineer to join our Data Labs (DL) department, which specializes in professional services for our super-premium customers. This role will report to our DL (Datalabs) Data Science Team Manager in the R&D.
So, what will you be doing all day?
Building and maintaining our big-data pipelines
Take a major part in designing and implementing complex high-scale systems using a large variety of technologies
Be part of a team with smart and motivated engineers, and data scientists, to collaborate on the planning, development, and maintenance of our products
Implement solutions in the AWS cloud environment, and work in Databricks with PySpark

We are looking for a Senior Data Platform Engineer to join our community!
As a Senior Data Platform Engineer, you will play a key role in building and evolving Grips modern data platform - the infrastructure that powers product features and analytics across the company.

You will focus on designing and operating scalable, reliable data systems and platform tooling that support our Data Lakehouse, enabling engineers, analysts and research teams to work with data efficiently and with minimal friction.

Responsibilities
Design, build and operate a cloud-native modern data platform.
Develop and optimize data processing frameworks and pipelines across batch and streaming workloads.
Improve developer experience and platform usability through tooling and automation.
Lead and support large-scale data migrations and architectural improvements.
Drive best practices around infrastructure, CI/CD, testing, and system design.
Collaborate with developers, analysts, data scientists and other stakeholders to develop new products and features.
Contribute to a strong engineering culture of ownership, learning, and knowledge sharing.

we are looking for a Senior Solutions Architect, Public Sector.
As a Solutions Architect at AWS, youll build technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey.
Youll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their challenging projects.
Internally, you will be the voice of the customer, sharing their needs and wants to inform the roadmap of AWS features.
Key job responsibilities:
In this role, your creativity will link technology to tangible solutions, with the opportunity to define or invent cloud-native reference architectures for a variety of use cases.
You will participate in the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts) and evangelize and educate about AWS technology (e.g. through workshops, user groups, meetups, public speaking, online videos or conferences).
If you can educate AWS customers about the art of the possible, while challenging the impossible, come build the future with us.
This role is within the Israel organization and you would be working with Public Sector customers.

We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build next-generation data stack.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll:
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals

We are looking for a Staff Data Platform Engineer to join our Engineering team and lead the evolution of our next-generation data platform. In this high-impact role, you will operate as a player-coach: you will be the technical visionary responsible for designing the ecosystem, while remaining deeply hands-on to implement scalable, secure, and intelligent solutions that power everything from operational reporting to advanced GenAI applications.
You will bridge the gap between complex business requirements and technical execution, advocating for a data-first culture. This role offers a clear growth path: while it currently starts as an individual contributor position, it has the potential to evolve into a leadership role.
About the Role:
Architecture & Hands-on Execution: Design and actively build a comprehensive data platform. You will not just oversee infrastructure; you will write the core code and build tools that support diverse workloads-from operational reporting to complex analytical queries.
Strategic & Technical Delivery: Partner with product managers to translate business objectives into technical strategies, then lead the engineering effort to deliver them.
Technology Evaluation: Continuously evaluate, prototype, and select best-in-class technologies to future-proof our data stack.
Technical Leadership & Mentorship: Act as a primary advocate for platform adoption. You will foster a community of practice around data engineering, mentoring senior and mid-level engineers to elevate the team's technical bar.
Governance & Quality: Implement and automate robust frameworks for Data Discovery, Quality, and Governance, ensuring solutions are trustworthy and compliant with financial regulations.

we are looking for a Senior Data Engineer I.
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.
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