Note: The job is a remote job and is open to candidates in USA. The client is a leader in AI testing seeking a skilled Data Engineer (AI Pipelines) for a 12-month contract engagement. The role focuses on building scalable ETL/ELT pipelines, ensuring data quality, managing large datasets, and optimizing data systems for AI training, inference, RAG, and real-time model serving.
Responsibilities
- Building scalable ETL/ELT pipelines to ingest, clean, and transform massive datasets for AI training and inference
- Implementing data quality checks and automated validation to prevent "garbage in, garbage out" in AI systems
- Managing the storage and versioning of large datasets using tools like DVC or Snowflake
- Optimizing data retrieval patterns for low-latency RAG systems and real-time model serving
- Collaborating with ML engineers to ensure data features are consistent across training and production
Skills
- 4+ years of experience in Data Engineering
- Deep expertise in SQL, Spark, Python, and modern data stack tools (Airflow, dbt). This isn't a learning role—you need to be a subject matter expert
- Demonstrated ability to work autonomously and manage your own time effectively to meet project goals
- Experience with cloud data warehouses (Snowflake, BigQuery) and Git
- Strong communication skills to provide clear and concise status updates to the project team
Benefits
- 12-month contract engagement
- Remote work
Company Overview