Responsibilities
- Design, construct, and operate scalable ETL/ELT pipelines that ingest telemetry, usage events, and business outcome data from diverse sources across the STT product portfolio
- Architect and implement a centralized data platform using AWS-native tools (Redshift, S3, Glue, Lake Formation, Lambda, Athena) to serve as the single source of truth for analytics
- Develop data models that connect product usage signals to business outcomes such as content effectiveness, field engagement, pipeline progression, and revenue impact
- Build data infrastructure to support AI/ML pipelines and agentic systems, including MCP tools and natural-language data access layers
- Establish data quality frameworks with automated monitoring, alerts, and validation to maintain accuracy as the platform scales
- Create self-service data products with clear SLAs, thorough documentation, and governance to reduce ad-hoc requests
- Collaborate with Applied Scientists and SDE teams to deliver clean, well-modeled data for agent evaluation frameworks, retrieval quality measurement, and content effectiveness scoring
- Set up data contracts, lineage tracking, and catalog metadata to promote discoverability and trust across the organization
- Operate with a strong standard for operational excellence, owning on-call responsibilities, monitoring pipeline health, and proactively addressing data freshness or quality issues
- Support the evolution from static dashboards toward agentic data systems by building foundational data layers that AI agents query and reason over
Requirements
- 3+ years of data engineering experience
- 3+ years designing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes
- 3+ years developing and maintaining large-scale BI data structures with SQL
- 3+ years of data modeling experience in BI contexts
- 3+ years in the offered role or a related occupation
Technologies
- Redshift
- S3
- Glue
- Lake Formation
- Lambda
- Athena
- EMR
- Kinesis
- Firehose
- I AM
Benefits
- Health insurance
- 401(k) matching
- Paid time off
- Parental leave
- Sign-on payments
- Restricted stock units (RSUs)
- Adoption and surrogacy reimbursement coverage
- Employee Assistance Program (EAP)
- Mental health support
- Flexible Spending Accounts
About the Team
You would join a high-growth engineering organization at the forefront of applying generative AI and agentic technologies to transform how AWS field teams operate. The centralized analytics team is being built from the ground up, and you will be among the first two Data Engineers on the team, collaborating with BI Engineers, a Senior BD, an Applied Scientist, and a TPM. You will help define foundational architectural decisions that shape how the platform is built, scaled, and operated.
Inclusive Team Culture
At AWS, curiosity and learning drive our work. Employee-led affinity groups foster inclusion and pride in our differences, with ongoing events and learning experiences such as CORE and AmazeCon that celebrate diversity and encourage ongoing openness to new perspectives.
Mentorship & Career Growth
AWS emphasizes continuous development as part of its mission to be Earth’s Best Employer. Expect ongoing knowledge sharing, mentorship, and resources designed to help you advance as a well-rounded engineering professional.
Work/Life Balance
Work life harmony is a priority, with flexibility as part of our culture to support performance without compromising home life. A supportive environment and balanced practices enable sustained cloud-focused achievement.
