Staff Data Engineer

Responsibilities

• Design, build, and maintain scalable data pipelines that process and transform large volumes of structured and unstructured data
• Manage ingestion from third-party APIs, internal systems, and customer datasets
• Develop and maintain data models, data schemas, and storage systems optimized for ML and product performance
• Collaborate with ML engineers to prepare model-ready datasets, embeddings, feature stores, and evaluation data
• Implement data quality monitoring, validation, and observability
• Work closely with product engineers to support new features that rely on complex data flows
• Optimize systems for performance, cost, and reliability
• Contribute to early architecture decisions, infrastructure design, and best practices for data governance
• Build tooling that enables the entire team to access clean, well-structured data

Requirements

• 3+ years of experience as a Data Engineer
• Proficiency in Python, SQL, and modern data tooling (dbt, Airflow, Dagster, or similar)
• Comfort working in fast, ambiguous environments
• Experience designing and operating ETL/ELT pipelines in production
• Experience with cloud platforms (AWS, GCP, or Azure)
• Familiarity with data lakes, warehouses, and vector databases
• Experience integrating APIs and working with semi-structured data (JSON, logs, event streams)
• Strong understanding of data modeling and optimization

Nice-to-haves

• Experience supporting LLMs, embeddings, or ML training pipelines
• Startup experience