Required Skills & Experience
3–8 years of overall data engineering experience, with a strong focus on AWSHands-on experience with AWS Lake Formation (data governance, permissions, LF-tags)Working knowledge of Amazon Neptune (graph modeling, Gremlin/SPARQL query experience preferred)Exposure to Amazon SageMaker for ML pipeline support (nice to have, not mandatory)Experience with Apache Airflow for workflow orchestrationStrong experience with core AWS data services: S3, Glue, Redshift, Athena, IAMProficiency in Python and SQL for data engineering tasksStrong communication skills; ability to work directly with client stakeholders