Role Summary

Build robust observable data pipelines that power research and production AI. Success means high pipeline reliability (on-time SLAs) strong data quality (validation & lineage) and enabling fast experimentation. You will partner with AI/ML analytics and product to make data trustworthy and usable.

Responsibilities

• Architect and operate batch/stream pipelines (Airflow; Spark optional) for ETL/ELT.
• Model/manage schemas; enforce data quality and lineage/governance.
• Support ML workflows with DVC (data versioning) and MLflow or Weights & Biases.
• Build feature stores/data services; expose datasets via secure REST endpoints.
• Optimize performance/cost across storage/compute; implement monitoring/alerting.
• Maintain documentation and internal catalogs; enable self-service analytics.

Qualifications

• Skills: Programming in C or Java; SQL & NoSQL; Pandas/NumPy...