Python Data Engineer

DUTIES AND RESPONSIBILITIES
- Design, build, and maintain ETL/ELT pipelines to collect, process end-to-end, and store financial data
- Write optimized, efficient code to process and analyze financial data
- Design and evolve the database schema; write and tune queries
- Build and maintain integrations with external data sources and APIs (market data feeds, vendor APIs, cloud storage)
- Identify and resolve performance bottlenecks
REQUIRED QUALIFICATIONS AND EXPERIENCE
- 1–2+ years designing and maintaining data pipelines, databases (SQL / PostgreSQL), and ETL processes
- Python with Pandas / NumPy and Git
- Comfortable working with cloud object storage — AWS S3 or GCP Cloud Storage (GCS)
- A solid understanding of or interest in financial data, instruments, and markets
- Intermediate English
NICE TO HAVE — BONUS, NOT EXPECTED
- Workflow orchestration: Airflow, Dagster, or Prefect
- Columnar / interchange formats: Parquet, Arrow, DuckDB
- Streaming or real-time feeds: Kafka, WebSocket market data
- Financial protocols / vendor APIs: FIX, Polygon, Refinitiv, Bloomberg
- Time-series databases: TimescaleDB, ClickHouse
- dbt, Docker, CI/CD
- Model Context Protocol (MCP) for AI/agent integrations
- Familiarity with R
- Background in Computer Science, Physics, or Applied Mathematics
WORK ENVIRONMENT
- Remote
- Flexible hours, 8 am – 8 pm
- Compassionate teammates and real growth opportunities
SALARY AND BENEFITS
- Paid vacation and state holidays (available to request after 8 months)
- Workshops and skills-boost courses encouraged