Data Engineer

Role overview Build and operate production data pipelines that support analytics and AI products. The role combines data ingestion and transformation, workflow orchestration, database performance work, and preparation of content for retrieval-augmented generation systems, in close collaboration with product, data science, and IT teams.

Responsibilities - Develop, optimize, and maintain ETL/ELT pipelines that move high-volume transactional data into SQL Server and PostgreSQL. - Create data ingestion, metadata, chunking, and embedding workflows for retrieval-augmented generation and automated detection use cases. - Schedule and monitor data workflows with tools such as Airflow, Azure Data Factory, or SQL Agent, adding checks to protect data quality. - Tune SQL queries and improve dimensional models and warehouse or lakehouse structures. - Use AI tools to support coding, modeling, and dataset design for analytics and AI workloads. - Work with product owners, data scientists, and operations colleagues to address production issues, support governance, and follow source control and delivery practices.

Requirements - At least three years of professional experience building and supporting production data pipelines. - Strong Python, including pandas, and SQL skills, including complex queries, window functions, and performance tuning. - Hands-on experience with SQL Server and PostgreSQL. - Experience orchestrating workflows with Airflow, Azure Data Factory, or SQL Agent; Azure cloud experience is preferred. - Understanding of dimensional modeling, lakehouse structures, and data preparation for AI, such as document ingestion, embeddings, or vector search. - Familiarity with Git, Bitbucket, Jira, and CI/CD practices; clear spoken and written English and availability to overlap with US Central business hours.

Nice to have Exposure to Docker and experience working with high-growth technology teams.

Benefits and work setup This is a fully remote US contractor role with USD compensation. The listing mentions paid time off and holidays, a health insurance assistance program, and opportunities to work with US-based clients and varied technology stacks. Engagement type is described as full-time or contractor.