Data Engineer

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves designing resilient ETL/ELT pipelines and data contracts to ensure datasets are analytics- and ML-ready. You’ll validate, enrich, and serve data with strong schema and versioning discipline, building the backbone that powers AI research and production systems. Build and maintain ETL/ELT pipelines with a focus on scalability and resilience. Validate and enrich datasets to ensure they’re analytics- and ML-ready. Manage schemas, versioning, and data contracts to maintain consistency. Work with PostgreSQL/SQLite, Spark/Duck DB, and Airflow to manage workflows. Optimize pipelines for performance and reliability using Python and pandas. Collaborate with researchers and engineers to ensure data pipelines align with product and research needs. Qualifications Have a background in computer science, data engineering, or information systems. Are proficient in Python, pandas, and SQL. Have hands-on experience with databases like PostgreSQL or SQLite. Understand distributed data processing with Spark or DuckDB. Are experienced in orchestrating workflows with Airflow or similar tools. Work comfortably with common formats like JSON, CSV, and Parquet. Care about schema design, data contracts, and version control with Git. Are passionate about building pipelines that enable reliable analytics and ML workflows. Requirements To design, validate, and maintain scalable ETL/ELT pipelines and data contracts that produce clean, reliable, and reproducible datasets for analytics and machine learning systems. Benefits You’ll be classified as an hourly contractor to Mercor. Paid weekly via Stripe Connect, based on hours logged. Part-time (20–30 hrs/week) with flexible hours—work from anywhere, on your schedule. Weekly Bonus of $500–$1000 USD per 5 tasks. Remote and flexible working style.