לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER בתל אביב יפו

Were looking for a Data Engineer to join our team and help shape a modern, scalable data platform. Youll work with cutting-edge AWS technologies, Spark, and Iceberg to build pipelines that keep our data reliable, discoverable, and ready for analytics.

Whats the Job?
Design and maintain scalable data pipelines on AWS (EMR, S3, Glue, Iceberg).
Transform raw, semi-structured data into analytics-ready datasets using Spark.
Automate schema management, validation, and quality checks.
Optimize performance and costs with smart partitioning, tuning, and monitoring.
Research and evaluate new technologies, proposing solutions that improve scalability and efficiency.
Plan and execute complex data projects with foresight and attention to long-term maintainability.
Collaborate with engineers, analysts, and stakeholders to deliver trusted data for reporting and dashboards.
Contribute to CI/CD practices, testing, and automation.

The Performance Marketing Analytics team is seeking a highly skilled Senior Data platform Engineer to establish, operate, and maintain our dedicated Performance Marketing Data Mart within the Snowflake Cloud Data Platform. This is a critical, high-autonomy role responsible for the end-to-end data lifecycle, ensuring data quality, operational excellence, and governance within the new environment. This role will directly enable the Performance Marketing team's vision for data-driven marketing and increased ownership of our analytical infrastructure
Responsibilities
Snowflake Environment Management
Administer the Snowflake account (roles, permissions, cost monitoring, performance tuning).
Implement best practices for security, PII handling, and data governance.
Act as the subject matter expert for Snowflake within the team.
DevOps & Model Engineering
Establish and manage the development and production environments.
Maintain CI/CD pipeline using GitLab to automate the build, test, and deployment process.
Implement normal engineering practices such as code testing and commit reviews to prevent tech debt.
Data Operations & Reliability
Monitor pipeline executions to ensure timely, accurate, and reliable data.
Set up alerting, incident management, and SLAs for marketing data operations.
Troubleshoot and resolve platform incidents quickly to minimize business disruption.
Tooling & Integration
Support the integration of BI, monitoring, and orchestration tools
Evaluate and implement observability and logging solutions for platform reliability.
Governance & Compliance
Ensure alignment with Entain data governance and compliance policies.
Document operational procedures, platform configurations, and security controls.
Act as the team liaison with procurement, infrastructure, and security teams for platform-related topics.
Collaboration & Enablement
Work closely with BI, analysts and data engineers, ensuring the platform supports their evolving needs.
Provide guidance on best practices for query optimization, cost efficiency, and secure data access.

We are looking for an exceptional Big Data Engineer to join our R&D team. This is a unique opportunity for a recent graduate or early-career engineer to enter the world of Big Data. You will work alongside the best engineers and scientists in the industry to develop systems that process and analyze data from around the digital world.
So what will you be doing all day?
Learn and Build: Assist in the design and implementation of high-scale systems using a variety of technologies, mentored by senior engineers.
Collaborate: Work in a data research team alongside data engineers, data scientists, and data analysts to tackle data challenges.
Optimize: Help improve the existing infrastructure of code and data pipelines and learn how to identify and eliminate bottlenecks.
Innovate: Experiment with various technologies in the domain of Machine Learning and big data processing.
Monitor: Assist in maintaining monitoring infrastructure to ensure smooth data ingestion and calculation.

Were looking for a Big Data Engineer to develop and integrate systems that retrieve, process and analyze data from around the digital world, generating customer-facing data. This role will report to our Team Manager, R&D.
Why is this role so important?
We are a data-focused company, and data is the heart of our business.
As a big data engineer developer, you will work at the very core of the company, designing and implementing complex high scale systems to retrieve and analyze data from millions of digital users.
Your role as a big data engineer will give you the opportunity to use the most cutting-edge technologies and best practices to solve complex technical problems while demonstrating technical leadership.
So, what will you be doing all day?
Your role as part of the R&D team means your daily responsibilities may include:
Design and implement complex high scale systems using a large variety of technologies.
You will work in a data research team alongside other data engineers, data scientists and data analysts. Together you will tackle complex data challenges and bring new solutions and algorithms to production.
Contribute and improve the existing infrastructure of code and data pipelines, constantly exploring new technologies and eliminating bottlenecks.
You will experiment with various technologies in the domain of Machine Learning and big data processing.
You will work on a monitoring infrastructure for our data pipelines to ensure smooth and reliable data ingestion and calculation.

Were looking for an Analytics Engineer to join our team and play a key role in shaping how data drives our product and business decisions.
This role is perfect for someone who enjoys working at the intersection of data, product, and strategy. While Product Analysts focus on turning data into insights, youll focus on building the strong data foundations that make those insights possible. You wont just run queries; you will design the data architecture and own the "source of truth" tables that power our strategic decision-making.
Youll work closely with our Growth and Solutions teams, helping them move faster and smarter by making sure the data behind Generative AI, Data-as-a-Service (DaaS), and advanced product models is clear, reliable, and easy to use. Your work will have a direct impact on how we build, scale, and innovate our products.
What Youll Do
Define the Source of Truth: Take raw, complex data and transform it into clean, well-structured tables that Product Analysts and Business Leads can use for high-stakes decision-making.
Translate Strategy into Logic: Work with Product, Growth, and Solutions leads to turn abstract concepts (like "Activation," "Retention," or "Feature Adoption") into precise SQL definitions and automated datasets.
Enable High-Tech Initiatives: Partner with our AI and DaaS specialists to ensure they have the structured data foundations they need to build models and external data products.
Optimize for Usability: Ensure our data is not just "there," but easy to use. You will design the data logic that powers our most important product dashboards and growth funnels.
Maintain Data Integrity: Act as the guardian of our metrics. You will ensure that the numbers used across our product and business reports are consistent, reliable, and logical.

We are looking for a Senior Data Platform Engineer to design, build, and scale next-generation data platform, the backbone powering our AI-driven insights.
This role sits at the intersection of data engineering, infrastructure, and MLOps, owning the architecture and reliability of our data ecosystem end-to-end.
Youll work closely with data scientists,r&d teams, analysts to create a robust platform that supports varying use cases, complex ingestion, and AI-powered analytics.
Responsibilities:
Architect and evolve a scalable, cloud-native data platform that supports batch, streaming, analytics, and AI/LLM workloads across R&D.
Help define and implement standards for how data is modeled, stored, governed, and accessed
Design and build data lakes and data warehouses
Develop and maintain complex, reliable, and observable data pipelines
Implement data quality, validation, and monitoring frameworks
Collaborate with ML and data science teams to connect AI/LLM workloads to production data pipelines, enabling RAG, embeddings, and feature engineering flows.
Manage and optimize relational and non-relational datastores (Postgres, Elasticsearch, vector DBs, graph DBs).
Build internal tools and self-service capabilities that enable teams to easily ingest, transform, and consume data.
Contribute to data observability, governance, documentation, and platform visibility
Drive strong engineering practices
Evaluate and integrate emerging technologies that enhance scalability, reliability, and AI integration in the platform.

We are looking for an experienced Data Engineering Team Leader.
In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.
A day in the life and how youll make an impact:
Drive the technical strategy and roadmap for the data engineering function, ensuring alignment with overall business objectives.
Own the design, development, and evolution of scalable, high-performance data pipelines to enable diverse and growing business needs.
Establish and enforce a strong data governance framework, including comprehensive data quality standards, monitoring, and security protocols, taking full accountability for data integrity and reliability.
Lead the continuous enhancement and optimization of the data analytics platform and infrastructure, focusing on performance, scalability, and cost efficiency.
Champion the complete data lifecycle, from robust infrastructure and data ingestion to detailed analysis and automated reporting, to maximize the strategic value of data and drive business growth.

We are looking for an expert Data Engineer to build and evolve the data backbone for our R&D telemetry and performance analytics ecosystem. Responsibilities include processing raw, large quantities of data from live systems at the cluster level: hardware, communication units, software, and efficiency indicators. Youll be part of a fast paced R&D organization, where system behavior, schemas, and requirements evolve constantly. Your mission is to develop flexible, reliable, and scalable data handling pipelines that can adapt to rapid change and deliver clean, trusted data for engineers and researchers.
What youll be doing:
Build flexible data ingestion and transformation frameworks that can easily handle evolving schemas and changing data contracts
Develop and maintain ETL/ELT workflows for refining, enriching, and classifying raw data into analytics-ready form
Collaborate with R&D, hardware, DevOps, ML engineers, data scientists and performance analysts to ensure accurate data collection from embedded systems, firmware, and performance tools
Automate schema detection, versioning, and validation to ensure smooth evolution of data structures over time
Maintain data quality and reliability standards, including tagging, metadata management, and lineage tracking
Enable self-service analytics by providing curated datasets, APIs, and Databricks notebooks.

Design, implement, and maintain robust data pipelines and ETL/ELT processes on GCP (BigQuery, Dataflow, Pub/Sub, etc.).
Build, orchestrate, and monitor workflows using Apache Airflow / Cloud Composer.
Develop scalable data models to support analytics, reporting, and operational workloads.
Apply software engineering best practices to data engineering: modular design, code reuse, testing, and version control.
Manage GCP resources (BigQuery reservations, Cloud Composer/Airflow DAGs, Cloud Storage, Dataplex, IAM).
Optimize data storage, query performance, and cost through partitioning, clustering, caching, and monitoring.
Collaborate with DevOps/DataOps to ensure data infrastructure is secure, reliable, and compliant.
Partner with analysts and data scientists to understand requirements and translate them into efficient data solutions.
Mentor junior engineers, provide code reviews, and promote engineering best practices.
Act as a subject matter expert for GCP data engineering tools and services.
Define and enforce standards for metadata, cataloging, and data documentation.
Implement monitoring and alerting for pipeline health, data freshness, and data quality.

This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from an HPE office.
Job Description:
We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.
This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutionsincluding the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.
What Youll Do
Architecture & Strategy
Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.
Engineering & Delivery
Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.
Leadership & Collaboration
Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.

We are looking for a highly motivated and experienced Data Engineering Team Lead to guide a global team responsible for building and maintaining the data infrastructure that powers our products. This team collaborates closely with software engineers, data scientists, product managers, analysts, and external partners to deliver scalable, high-quality data solutions that drive business impact.

Key Responsibilities

Lead a global team of software engineers, centered in Israel, operating under the Agile Scrum methodology.
Own the teams execution, quality, and alignment to data architecture and company-wide engineering standards.
Work together with product managers to define priorities for each sprint and align engineering efforts to business goals.
Guide the teams involvement in cross-functional projects alongside Software, ML, Analytics, and Partner teams.
Ensure secure, reliable, and efficient access to internal and third-party data sources across all products.
Actively participate in roadmap planning, resource allocation, and technical design reviews.
Provide mentorship, technical guidance, and growth opportunities to team members.

the Senior Data Engineer position is a central role in the Tech Org. The Data Engineering (DE) team is a Change Agent Team that plays a significant role in the ongoing (at advanced stages) migration of to cloud technologies. The ideal candidate is a senior data engineer with a strong technical background in data infrastructure, data architecture design and robust data pipes building. The candidate must also have collaborative abilities to interact effectively with Product managers, Data scientists, Onboarding engineers, and Support staff.
Responsibilities:
Deploy and maintain critical data pipelines in production.
Drive strategic technological initiatives and long-term plans from initial exploration and POC to going live in a hectic production environment.
Design infrastructural data services, coordinating with the Architecture team, R&D teams, Data Scientists, and product managers to build scalable data solutions.
Work in Agile process with Product Managers and other tech teams.
End-to-end responsibility for the development of data crunching and manipulation processes within the product.
Design and implement data pipelines and data marts.
Create data tools for various teams (e.g., onboarding teams) that assist them in building, testing, and optimizing the delivery of the product.
Explore and implement new data technologies to support data infrastructure.
Work closely with the core data science team to implement and maintain ML features and tools.