About the Role

The Data Engineer I role involves developing and maintaining ETL pipelines for FBA metrics to support a GenAI-powered insights assistant. This position focuses on optimizing data infrastructure for AI-driven querying and ensuring data quality and freshness.

Key Responsibilities

• Develop and maintain ETL pipelines in Spark to transform and load FBA metrics into the Data Lakehouse
• Optimize SQL queries for fast, cost-efficient access by AI systems
• Support dbt semantic models and automate metadata enrichment with Glue
• Write automated tests to ensure data quality and freshness
• Build pipelines that add business context metadata to help AI generate accurate SQL queries

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.
• Proficiency in dbt, Airflow/MWAA, AWS Glue, Kinesis
• Experience building semantic layers or BI models
• Familiarity with prompt-driven SQL generation and AI-assisted query validation