Data Engineer

You will build, operate, and improve data pipelines that support analytics and model training. You will prepare agentic data for analysis and training, design schemas and data models, select ETL or ELT approaches, and manage production pipeline operations, including failures, re-runs, backfills, and debugging.

Responsibilities

• Build, operate, and continuously improve data pipelines for analytics and model training
• Deliver reliable internal analytics
• Wrangle agentic data into structured, documented datasets
• Choose and explain ETL and ELT approaches
• Own production pipeline failures, re-runs, backfills, and debugging
• Design and evolve schemas, storage formats, and data models
• Build memory-efficient processing with streaming and partitioning
• Communicate data location, lineage, quality, limitations, and fitness for use

Requirements

• 4+ years of data engineering experience building and operating production data pipelines
• SQL, data modeling, and schema design and evolution
• Understanding of storage formats and database types
• Understanding of data ingestion, storage, transformation, orchestration, cataloging, and serving
• Python and shell skills
• Cloud experience with object storage, batch compute, and identity and access management
• Production experience with a workflow orchestration system such as Airflow, Dagster, or Prefect
• Data quality expertise
• Experience using AI-assisted development tools with disciplined review