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

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.

What Youll Be Doing:
Help improve our analytics practices by gathering better data, making it more trustworthy and accessible, and nurturing a top-grade data culture across the company.
Design, develop, scale, and optimize the data pipelines, ETLs and various data models.
Use SQL, DBT, Python and any other relevant tools and technologies.
Identify blind spots in how we use data and lead initiatives to illuminate them.
Collaborate with various stakeholders across the company to translate requirements into high-quality data pipelines and models.
We are currently rebuilding and redesigning much of our tech-stack and processes. Play a major role in designing the future data-work within the company.

We are seeking a Data Engineer to join our dynamic data team. In this role, you will design, build, and maintain robust data systems and infrastructure that support data collection, processing, and analysis. Your expertise will be crucial in developing scalable data pipelines, ensuring data quality, and collaborating with cross-functional teams to deliver actionable insights.

Key Responsibilities:
Design, develop, and maintain scalable ETL processes for data transformation and integration.
Build and manage data pipelines to support analytics and operational needs.
Ensure data accuracy, integrity, and consistency across various sources and systems.
Collaborate with data scientists and analysts to support AI model deployment and data-driven decision-making.
Optimize data storage solutions, including data lakehouses and databases, to enhance performance and scalability..
Monitor and troubleshoot data workflows to maintain system reliability.
Stay updated with emerging technologies and best practices in data engineering.

Please note that this role is on a hybrid model of 4 days/week in our Tel-Aviv office.

We are hiring a Staff Data AI Lead to lead our AI initiatives.As a Staff Data AI Lead you will be responsible for leading SuperSonic organization AI integration efforts and serving as the bridge between advanced AI technologies and our business needs, implementing cutting-edge Data & AI technologies, creating AI-driven strategies and integrating innovative AI solutions across multiple platforms.
What you'll be doing
Develop and execute AI strategies aligned with business objectives
Advise leadership on AI capabilities and potential applications
Guide teams in adopting AI tools and methodologies
Ensure ethical and efficient implementation of AI technologies
Design and oversee AI-driven process improvements
Collaborate with various departments to identify AI opportunities
Stay current with the latest AI trends and advancements
Conduct AI-related training and workshops for staff
Manage AI projects from conception to implementation
Evaluate and recommend AI tools and platforms
Leading a team of AI engineers.

We are looking for a hands-on data infrastructure and platform engineer with proven leadership skills to lead and evolve our self-service data platform that powers petabyte-scale batch and streaming, near-real-time analytics, experimentation, and the feature platform. Youll guide an already excellent team of senior engineers, own reliability and cost efficiency, and be the focal point for pivotal, company-wide data initiatives- feature platform, lakehouse, and streaming.
Own the lakehouse backbone: Mature Iceberg at high scalepartitioning, compaction, retention, metadataand extend our IcebergManager in-house product to automate the lakehouse management in a self serve fashion.
Unify online/offline for features: Drive Flink adoption and patterns that keep features consistent and low-latency for experimentation and production.
Make self-serve real: Build golden paths, templates, and guardrails so product/analytics/DS engineers can move fast safely.
Run multi-tenant compute efficiently: EMR on EKS powered by Karpenter on Spot instances; right-size Trino/Spark/Druid for performance and cost.
Cross-cloud interoperability: BigQuery + BigLake/Iceberg interop where it makes sense (analytics, experimentation, partnership).
What you'll be doing
Leading a senior Data Platform team: setting clear objectives, unblocking execution, and raising the engineering bar.
Owning SLOs, on-call, incident response, and postmortems for core data services.
Designing and operating EMR on EKS capacity profiles, autoscaling policies, and multi-tenant isolation.
Tuning Trino (memory/spill, CBO, catalogs), Spark/Structured Streaming jobs, and Druid ingestion/compaction for sub-second analytics.
Extending Flink patterns for the feature platform (state backends, checkpointing, watermarks, backfills).
Driving FinOps work: CUR-based attribution, S3 Inventory-driven retention/compaction, Reservations/Savings Plans strategy, OpenCost visibility.
Partnering with product engineering, analytics, and data science & ML engineers on roadmap, schema evolution, and data product SLAs.
Leveling up observability (Prometheus/VictoriaMetrics/Grafana), data quality checks, and platform self-service tooling.

We are looking for a talented and experienced Data Engineer to join our data group.
The team is responsible for processing and transforming data from multiple external sources while building and maintaining an internal serving platform. Our key challenges include operating at scale, integrating with diverse external interfaces, and ensuring the data is served in a consistent and reliable manner.
Responsibilities
Designing and implementing our data platform
Transforming, modeling, and serving all our medical data.
Utilize data best practices, to improve the product and allow data-driven decision-making.
Collaborate closely with cross-functional teams to understand business requirements and translate them into data-driven solutions.
Stay updated with the latest research and advancements in the data field.

We are looking for a talented Architect to join us. As a Data Architect, you will be the organizational point of contact for all things related to data persistence and architecture. You will work closely with engineering teams across the Product, Platform, and Data groups to design, govern, and evolve our data models, databases, and data-related systems. Your goal will be to ensure scalability, reliability, security, and efficiency for all data storage and retrieval across the organization.
A few of the things you will do:
Be the primary point of contact and subject matter expert for data persistence across the entire engineering organization.
Define and govern the data architecture strategy, standards, and best practices for relational, NoSQL, and data warehouse systems.
Partner with engineering teams from product, platform, and data groups to design and implement scalable and robust data models for new and existing services.
Lead the design and optimization of the organizations data flows. You will help to ensure that data moves efficiently, consistently, and with high quality across all systems and domains.
Evaluate and recommend new technologies and data solutions to meet evolving business needs.
Drive initiatives to improve data quality, consistency, and integrity across all production systems, from ideation to hands-on execution.
Establish, maintain, and communicate documentation for all data models and architectural decisions.

Join a team that builds and operates the core data services behind products.
As a Senior Data Engineer, you will design, build and maintain:
Data pipelines and data services
Microservices and internal APIs
The infrastructure and tooling that keep our data systems reliable, observable, and scalable
This is a hands-on role that combines Data Engineering, Backend Development and DevOps.
Its ideal for someone who enjoys working across layers: from schema design and data flows, through microservice code, to Kubernetes, CI/CD and observability.
Responsibilities:
Design and maintain robust infrastructure for large-scale data processing and streaming systems.
Develop automation and deployment processes using CI/CD pipelines.
Build and operate Kubernetes-based environments and containerized workloads.
Collaborate with data engineers to optimize performance, cost, and reliability of data platforms.
Design and develop REST-API microservices.
Troubleshoot and resolve complex issues in production and staging environments.
Drive initiatives that enhance observability, scalability, and developer productivity.
Lead by example - share knowledge, mentor teammates, and promote technical best practices.

Were looking for a highly skilled Senior Database Engineer to join our DBA team. In this role, youll design and optimize our large-scale database infrastructure while ensuring high availability, scalability, and performance. In your day-to-day, you will:
Design and optimize our large-scale database infrastructure to meet high availability and performance standards
Identify cost-effective areas for improvement in current databases
Collaborate with developers and software architects to model, create, and maintain robust data structures and the data layer
Lead and execute technical database-related POCs and benchmarks
Conduct regular audits of database design to ensure quality and compliance with service level agreements (SLAs)
Quickly identify and resolve critical production issues and provide on-call support as needed.

We are seeking a Data Engineering Lead to own and scale data platform infrastructure

Build our new data Lakehouse to support various product and business needs
Support cutting-edge AI Agents and cybersecurity use cases
Be part of the Data and AI Algorithms group
Collaborate closely with dev teams, AI/ML engineers, security researchers and business teams
Ensure the availability, reliability and quality of our data infrastructure
Help define best practices for data modeling and orchestration at scale

We are looking for an experienced BI / Data Engineer to develop systems that make vast amount of data more accessible and efficient throughout the organization. This is a perfect opportunity if youre passionate about data and have strong analytical and technical skills.

You will be developing innovative and creative ways to deliver data and information at scale in a fast-growing, exciting industry while working closely with our data analysts, product managers, software engineering teams, and management.

Responsibilities:

Design, manage, and optimize scalable data models and BI infrastructures for internal and external stakeholders
Work with diverse relational and non-relational databases (Presto, Athena, Firebolt, MySQL, etc.)
Build and maintain reliable ETL/ELT pipelines using Airflow, Python, and Upsolver
Design and develop data visualizations and dashboards (Tableau)
Identify and implement technological solutions for large-scale analytics
Serve as the central data authority, providing guidance, documentation, and support across the company

we are looking for a Analytics Engineer.
What Youll Do:
Work cross-functionally with Product, Engineering, Leadership and Design teams to deeply understand business needs and translate them into data requirements, well-defined metrics, and analytical tools to enable KPI tracking
Design, build, and maintain scalable, reliable data models and infrastructure to support analytics, operations, and product use cases
Champion data quality, documentation, and execution to ensure observability and trust across the organization
Own all data aspects of the flights team line of business
Spearhead AB testing development and implementation to increase deployment trust.
Support ongoing and adhoc analyses to ensure business goals are met and to uncover areas of opportunity

Were looking for a versatile, talented, and highly motivated Data Engineer to join our growing team.

If youre passionate about solving complex problems, thrive in dynamic environments, and love working at the intersection of data engineering, machine learning infrastructure, and AI innovation, this role is for you.

As a Data Engineer, youll play a key role in shaping how data flows through the company, from building scalable pipelines and robust infrastructure to powering data science models and enabling internal teams with intelligent GenAI-powered tools. This is a hands-on, high-impact role with plenty of room for ownership, creativity, and growth.

This is a high-impact role where your work will shape how the company leverages data and AI. If you want to build, innovate, and push boundaries in a collaborative and fast-moving environment, wed love to meet you.

Responsibilities
Own the entire data lifecycle from understanding business needs and building reliable pipelines to ensuring data quality, observability, and performance.
Design, build, and scale modern data infrastructure including data lakes, warehouses, and complex ETL/ELT pipelines.
Integrate and consolidate diverse data sources (CRMs, APIs, databases, SaaS platforms) into a single, trusted source of truth.
Implement and manage CI/CD, observability, and infrastructure-as-code in a cloud-native environment.
Work with the data science team on their ML pipelines, giving data scientists the infrastructure and automation they need to deploy models to production with speed and confidence.
Collaborate with cross-functional teams to embed GenAI agents into business processes, creating smart workflows that boost efficiency and reduce manual work.
Develop frameworks and internal tooling that empower other teams to safely adopt AI and accelerate innovation.
Optimize data infrastructure for performance and cost-efficiency, with a focus on BigQuery optimization.
Ensure high data quality and integrity across large-scale ETL processes. Work closely with analysts, data scientists, and product managers to support data modeling, governance, and analytical initiatives.