About the Role

This Data Engineer I role supports the GenAI-powered insights assistant by building pipelines that process unstructured data in the S3 Data Lakehouse. The position involves managing vector databases for embeddings and working on one of Amazon's largest analytics ecosystems.

Key Responsibilities

• Develop metadata pipelines to tag documents with freshness and ownership
• Implement caching and multi-region replication to reduce query latency
• Monitor data retrieval accuracy and log source citations to improve AI trustworthiness
• Automate ingestion and embedding generation for unstructured data into vector databases

Required Skills & Qualifications

Must Have:

• 1+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
• Experience with one or more scripting language (e.g., Python, KornShell)

Nice to Have:

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
• Strong expertise in AWS Glue, Redshift, Kinesis/MSK, Lambda
• Hands-on with data contracts, lineage tracking, and automated QA
• Familiarity with multi-modal data ingestion (structured + unstructured)
• Experience operationalizing cross-region replication and caching strategies