Who We Are

At Partnerize, we're on a mission to transform the way businesses grow. We've built the leading partnership automation platform that empowers brands to discover, engage, and convert their audiences at scale. From affiliate marketing to influencer collaborations, we help our clients build and manage profitable partnerships that drive real results. We're a team of passionate problem-solvers who are dedicated to helping our clients win in the ever-evolving world of digital marketing.

Why Join Us

We're looking for passionate, talented people who want to be part of a winning team. At Partnerize, you'll find a culture of collaboration, innovation, and respect. We're guided by our core values, and we're committed to creating an environment where everyone can do their best work. We also offer a competitive salary, generous benefits, and a flexible work environment that allows you to thrive both personally and professionally. If you're ready to grow your career and make a difference, we'd love to hear from you.

About the Role

Partnerize is a global leader in partnership automation, helping the world’s leading brands discover, manage, and optimize their partnerships at scale.

Our Tel Aviv R&D team builds advanced data and AI-driven products that analyze massive volumes of consumer journey, attribution, and digital ecosystem data. We combine large-scale data engineering, machine learning, and analytics to uncover signals and insights that traditional measurement systems cannot see.

We’re looking for a talented and highly motivated Senior Data Engineer to join our team and help build the data infrastructure powering our next generation of attribution and AI-driven products.

You’ll work closely with Data Scientists, Software Engineers, Product Managers, and DevOps Engineers to design and build scalable data pipelines and infrastructure capable of processing large and complex datasets.

What You’ll Do

Design, build, and own highly scalable data pipelines and data infrastructure.
Process and analyze large-scale datasets from multiple digital sources and environments.
Build reliable infrastructure and reusable components that enable Data Scientists and Product teams to develop and productionize data-driven capabilities.
Design data architectures optimized for scalability, reliability, performance, and cost.
Develop production-grade data processing systems handling high volumes of structured and unstructured data.
Work closely with Data Scientists to turn analytical models and experiments into scalable production systems.
Shape and standardize our data engineering approach, architecture, tooling, and best practices.
Evaluate and introduce new technologies where they can materially improve our data platform.
Monitor, optimize, and continuously improve the performance and reliability of our data infrastructure.
Collaborate across Product, Engineering, Data Science, and DevOps from early-stage problem definition through production deployment.

What You’ll Need

Strong hands-on experience in Data Engineering or large-scale backend/data-intensive systems.
Solid software engineering fundamentals, including system architecture and design.
Proven experience designing and building scalable data pipelines in production.
Strong experience working with cloud environments; AWS experience is required.
Experience with modern data technologies such as Airflow, Spark, Flink, Redshift, Athena, Iceberg, Parquet, Glue, Firehose, and Kinesis, or comparable technologies.
Experience working with large datasets and distributed data processing systems.
Strong understanding of data modeling, data quality, performance optimization, and reliability.
Ability to independently own complex technical problems from architecture through production.
Strong communication and collaboration skills.
Curiosity and the ability to quickly learn and evaluate new technologies.

Nice to Have

Experience building infrastructure supporting Machine Learning or Data Science workloads.
Experience with digital advertising, attribution, marketing technology, or large-scale behavioral datasets.