7+ years of experience as a Data Engineer or Architect or in a similar data-focused role, with clear ownership of end-to-end data solutions. Strong expertise in writing and optimizing complex SQL queries (advanced joins, aggregations, performance tuning). Proven experience building and maintaining Airflow DAGs (or similar orchestration tools), focused on workflow logic, code, and SQL rather than infrastructure. Deep understanding of data modeling principles, including designing datasets at the correct grain and preventing data inconsistencies. Use of the medallion model. Strong ability to understand business needs and translate them into scalable, maintainable data solutions. Demonstrated experience debugging data issues and tracing discrepancies in critical business metrics across pipelines. Proficient in Python for orchestration and data workflows. Comfortable reading and reasoning about existing code, SQL, DAGs, schemas, and input data formats (e.g., JSON). Experience working with cloud data warehouses such as Snowflake, BigQuery, or Databricks. Experience in Snowflake and its extended SQL and nuances is a strong advantage.
