Lead development of scalable, algorithm-heavy data products using PySpark and Implement and maintain complex, multi-stage data flows with multiple interacting algorithms.
Translate business and algorithmic requirements into clear, testable data logic. Ensuring explainability of outputs through intermediate artifacts, metadata, and documentation & Defining and monitoring; observability signals for data quality, algorithm health, and business impact.
Mentor engineers on reasoning about complex logic, edge cases, and failure modes.
2+ years of experience in technical leadership or leading complex projects.
6+ years of experience as a Data / Backend Engineer in data-intensive systems.
Strong production experience with PySpark.
Excellent SQL skills for complex analysis, validation, and BI-facing data models.
Proven experience implementing complex algorithms and business logic at scale.
Strong understanding of data correctness, edge cases, and validation strategies.
Advantage
Experience with algorithm explainability and data observability.
Background working closely with Data Science / ML teams.
Experience with large-scale Spark batch or streaming pipelines.
AWS-based data platforms experience.
* משרה זו פונה לנשים וגברים כאחד.