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Data Engineering Manager
·Israel
Not specifiedFull-timeData EngineeringMessaging
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment, owning the design and evolution of a self-service data platform. Architect batch and streaming pipelines, drive production ML systems, and ensure reliability, scalability, and observability of large-scale data and ML systems.
Responsibilities
- Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
- Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
- Architect and scale batch and streaming pipelines powering core business and ML use cases.
- Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
- Ensure reliability, scalability, and observability of large-scale data and ML systems in production.
Requirements
- 3+ years of engineering management experience leading Data / ML / Software engineering teams in production environments.
- 6+ years of experience building large-scale distributed systems in Data Engineering, ML Engineering, or Software Engineering roles.
- Proven ownership of production-grade data or ML platforms, including delivery and adoption across R&D and Product stakeholders.
- Hands-on experience building and operating high-scale distributed data systems (Spark, Storm, Flink) in production.
- Strong experience with Java and Python in AWS cloud environments.
Nice to have
- Proven track record leading multi-disciplinary teams and driving measurable business impact through data/ML systems.
- Experience building ML platforms, feature stores, or self-serve data infrastructure at scale.
- Deep experience with modern ML/infra stack (PyTorch, TensorFlow, SageMaker, Kubernetes, Argo).
- Experience with modern data lakehouse and analytics stack (Iceberg, Athena, ClickHouse, data catalogs, data quality frameworks).
- Experience deploying LLM-based systems or AI-driven infrastructure in production environments.