Data Engineer II, WW FBA Central Analytics
Teknik, data och digitalt · Data, AI och analys · Data engineering · Datavetenskap
I korthet
The WW FBA Central Analytics team seeks a Data Engineer II to build and maintain data infrastructure for an LLM-based insights platform. This role focuses on implementing data standardization, governance, and metadata enrichment to ensure AI-generated insights are accurate and trustworthy, designing systems for schema standards, lineage tracking, and quality validation.
Ansvarsområden
- Build dbt-based semantic models representing FBA metrics with business-friendly definitions consumed by RAG.
- Automate metadata harvesting with column-level descriptions, ownership tags, and business context for retrieval during text-to-SQL prompts.
- Implement lineage tracking tied to Redshift, S3, and Glue to power AI-driven source citations.
- Implement fine-grained access controls for embeddings and vector DB access, enforcing compliance.
- Build pipelines for proactive quality validation (null checks, distribution anomalies) feeding into AI's feedback loops.
- Partner with teams on metric standardization initiatives to avoid ambiguity in AI responses.
Krav
- 5+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
- 5+ years in data engineering with experience in AWS and data quality tooling.
- Proficiency in SQL, Python, and workflow orchestration (MWAA/Airflow).
- Strong knowledge of data quality frameworks.
Önskade kvalifikationer
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Familiarity with LLM-driven metadata retrieval and semantic layer development.
- Experience with audit and lineage tools.
Förmåner
- Inclusive culture empowers Amazonians to deliver the best results for our customers.
- Workplace accommodations and adjustments available during the application and hiring process, including support for the interview or onboarding process.
#Data Engineering#Analytics#AWS#LLM#Fulfillment by Amazon#ETL#Data Quality#Metadata#Data Modeling