Senior Quant Data Engineer to $6500

• Experience: 6+ years in Data Engineering in finance industry
• Core Stack: Expert Python, Spark, Airflow, and Snowflake/Databricks.
• Cloud: AWS (S3-based data lakes and delivery).
   

Technical Focus

• Quant Data Modeling: Architecting Point-in-Time (PIT) compliant datasets to eliminate look-ahead bias and data leakage in backtesting.
• Time-Series Management: Handling late-arriving data, "as-of" versioning, and anomaly detection for panel datasets.
• ETL at Scale: Building high-throughput pipelines that standardize raw alternative/financial data into analysis-ready formats.
• External Delivery: Engineering production feeds for institutional clients via Snowflake Share, Delta Sharing, and APIs.

Key Skills

• Advanced schema design and metadata management.
• Experience with data validation/monitoring for high-stakes systematic trading environments.
• Ability to translate between technical engineering and quantitative research requirements.