לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER

We're in search of an experienced and skilled Senior Data Engineer to join our growing data team. As part of our data team, you'll be at the forefront of crafting a groundbreaking solution that leverages cutting-edge technology to combat fraud. The ideal candidate will have a strong background in designing and implementing large-scale data solutions, with the potential to grow into a leadership role. This position requires a deep understanding of modern data architectures, cloud technologies, and the ability to drive technical initiatives that align with business objectives.
Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud.
Your Arena
Design, develop, and maintain scalable, robust data pipelines and ETL processes
Architect and implement complex data models across various storage solutions
Collaborate with R&D teams, data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality solutions
Ensure data quality, consistency, security, and compliance across all data systems
Play a key role in defining and implementing data strategies that drive business value
Contribute to the continuous improvement of our data architecture and processes
Champion and implement data engineering best practices across the R&D organization, serving as a technical expert and go-to resource for data-related questions and challenges
Participate in and sometimes lead code reviews to maintain high coding standards
Troubleshoot and resolve complex data-related issues in production environments
Evaluate and recommend new technologies and methodologies to improve our data infrastructure.

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 talented and experienced Data QA Engineer to join our data team. In this role, you will be responsible for ensuring the quality of the data we collect from websites. You will work closely with the development team, data analysts, Project Managers etc. to ensure that the data meets the highest standards of accuracy, integrity, and consistency.
Responsibilities
Planning, developing, and executing comprehensive test scenarios for data clients, that are based on public Web data:
Designing tests for client data needs, based on manual and automated methods
Performing manual and automated testing of data - integrity, accuracy etc.
Leveraging SQL to retrieve and analyze data from various databases
Documenting and tracking bugs and data quality issues
Analyzing large data sets to identify trends, anomalies, and potential problems
Communicating test findings clearly and effectively to various stakeholders
Defining QA standards and tools for partners developing data scrapers or performing basic QA testing for data:
Designing tests for different types of data being collected online
Building automated tests where relevant
Documenting methods and tools
Training the partners as needed
Validating the partner QA effectiveness
Developing and maintaining automated testing tools and scripts
Working closely with team members to ensure that the QA meets business and technical requirements
Staying updated with new testing technologies and methodologies.

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.

A fast-growing fintech AI start-up company, focused on eliminating fraud and chargebacks in online commerce, is looking for an experienced Senior Data Engineer.
In this Roll, you will build large-scale, cutting-edge data solutions for fraud prevention, with the potential to grow into a technical leadership role.
The company is located in Modi'in, central Israel. Hybrid work model.
Responsibilities
Build and maintain scalable data pipelines and ETL processes.
Design complex data models and optimize data architecture.
Collaborate with teams to deliver high-quality, compliant solutions.
Troubleshoot production issues and implement best practices.
Recommend new technologies to enhance the data infrastructure.

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 seek a highly skilled and experienced Solution Architect with a deep understanding of Data and operations to join our team. In this role, you will be responsible for designing and implementing data-centric solutions that enable our customers to achieve their business objectives, with a strong focus on building efficient and reliable ETL pipelines. You will work closely with clients to understand their needs, translate them into technical requirements, and architect scalable, reliable, and secure data pipelines.
Key Responsibilities:
Collaborate with clients to gather requirements and understand their data
challenges.
Design and implement end-to-end DataOps solutions, including data
ingestion, processing, storage, and analysis.
Leverage cloud technologies and best practices to architect scalable and
cost-effective data architectures.
Ensure data quality, integrity, and security throughout the data lifecycle.
Automate data pipelines and workflows to improve efficiency and reduce
manual effort.
Stay up-to-date with the latest DataOps trends and technologies.
Provide technical guidance and mentorship to other team members.

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.

We're looking for a DataOps Engineer to join our DataOps team, part of the DevOps & Infrastructure group. In this role, you will ensure the performance, reliability, and scalability of our large-scale (multi-terabyte) database systems that underpin the platform. You will be implementing best practices for database infrastructure, improving complex query performance, security, and maintenance. If you are passionate about data, building complex infrastructure and collaboration in a fast-paced environment, this role will be a great fit for you.
How Youll Spend Your Day
Manage, maintain and monitor our ClickHouse, Microsoft SQL Server, PostgreSQL, and OpenSearch databases, ensuring HA, backups, and proper security measures to protect data integrity
Use scripting tools (Python, Bash, PowerShell) to automate regular database and CI/CD tasks.
Collaborate closely with R&D, Security, and Product teams to enhance data infrastructure
Help plan migrations or deployments of database systems to the cloud when needed