Based in Austin, TX, this onsite data engineering role at Amazon Web Services, Inc. centers on designing, building, and operating scalable ETL and ELT pipelines and a centralized data platform that links product telemetry, usage metrics, and business outcomes. The position emphasizes robust data infrastructure while BI engineers handle reporting and stakeholder analytics to enable self-service insights for thousands of AWS field team members.
Compensation
Salary: USD 132,100 – 196,600 per year.
Responsibilities
- Design, implement, and operate scalable ETL/ELT pipelines to ingest product telemetry, usage events, and business outcome data from diverse sources across the STT product portfolio.
- Architect a centralized data platform using AWS native services (Redshift, S3, Glue, Lake Formation, Lambda, Athena) to serve as the authoritative source of analytics.
- Develop and maintain data models linking product usage signals to business outcomes such as content effectiveness, field engagement, pipeline progression, and revenue impact.
- Build data infrastructure that supports AI/ML pipelines and agentic systems, including MCP tooling and natural language data access layers.
- Implement data quality frameworks with automated monitoring, alerts, and validation to ensure accuracy and reliability as the platform scales.
- Create self-service data products with clearly defined SLAs, documentation, and governance to reduce ad hoc requests and empower stakeholders to answer their own questions.
- Collaborate with Applied Scientists and SDE teams to provide clean, well-modeled data for agent evaluation frameworks, retrieval quality measurement, and content effectiveness scoring.
- Establish data contracts, lineage tracking, and catalog metadata to support discoverability and trust across the organization.
- Operate with a high bar for operational excellence, including on-call ownership, monitoring pipeline health, and proactively addressing data freshness or quality issues before they impact consumers.
- Contribute to the evolution from static dashboards toward agentic data systems by building foundational data layers that AI agents query and reason over.
Requirements
- At least 3 years of data engineering experience.
- A minimum of 3 years building and operating large-scale BI data structures using ETL/ELT processes.
- At least 3 years developing and operating large-scale BI data structures with SQL.
- At least 3 years developing and operating large-scale BI data structures with data modeling.
- 3+ years of relevant work experience in the offered role or a related occupation.
Technologies
- Redshift
- S3
- Glue
- Lake Formation
- Lambda
- Athena
- EMR
- Kinesis
- FireHose
- IAM
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 will 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 Business Intelligence Engineers, a Senior BD, an Applied Scientist, and a TPM. You will help shape foundational architectural decisions that define how the platform will be built, scaled, and operated.
Inclusive Team Culture
At AWS, curiosity and learning are foundational. Employee-led affinity groups promote inclusion and empower us to celebrate our differences. Ongoing events and learning experiences, including CORE (Conversations on Race and Ethnicity) and AmazeCon (gender diversity), inspire continuous engagement with our diverse community.
Mentorship & Career Growth
We pursue continuous improvement as part of AWS efforts to become Earth’s Best Employer. The organization offers extensive knowledge-sharing, mentorship, and other resources to advance professional development.
Work/Life Balance
We value work life harmony and support flexibility as part of our culture. When employees feel supported at work and at home, they can achieve success in the cloud together.
