Data Engineer - ETL Pipelines & AI Platform (Austin)

Amazon Web Services, Inc.; Austin (TX); On-site; USD 132,000 - 197,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Sign-on payments

Restricted stock units (RSUs)

Adoption and surrogacy reimbursement

Employee Assistance Program (EAP)

Mental health support

Flexible Spending Accounts

Job summary

Amazon Web Services, Inc. in Austin, TX is seeking an on-site Data Engineer to design, build, and operate scalable ETL/ELT pipelines that ingest product telemetry, usage events, and business data across the STT portfolio.

You will join a growing analytics team, work with BI engineers and scientists to shape a centralized data platform using AWS services, implement data models linking usage signals to business outcomes, and contribute to data quality and self-serve analytics for thousands of AWS

Qualifications

• 3+ years of data engineering experience.
• 3+ years designing and operating large scale BI data structures using ETL/ELT processes.
• 3+ years developing and maintaining large scale BI data structures using SQL.
• 3+ years of data modeling experience for BI analytics.
• 3+ years in the job offered or a related occupation.

Responsibilities

• Design, build, and operate scalable ETL and ELT pipelines that ingest product telemetry, usage events, and business outcome data from multiple sources across the STT product portfolio.
• Architect and implement a centralized data platform using AWS native technologies such as Redshift, S3, Glue, Lake Formation, Lambda, and Athena to serve as the single source of truth for analytics.
• Develop data models that connect product usage signals to business outcomes like content effectiveness, field engagement, pipeline progression, and revenue impact.
• Build data infrastructure to support AI and ML pipelines and agentic systems, including MCP tools and natural language data access layers.
• Establish data quality frameworks with automated monitoring, alerting, and validation to ensure accuracy as the platform scales.
• Create self-service data products with clear SLAs, documentation, and governance to reduce ad hoc requests and empower stakeholders.
• Partner with Applied Scientists and SDE teams to provide clean, well modeled data for agent evaluation frameworks, retrieval quality measurement, and content effectiveness scoring.
• Define data contracts, lineage tracking, and catalog metadata to support discoverability and trust.
• Maintain a high bar for operational excellence, including on call ownership, pipeline health monitoring, and proactive resolution of data freshness or quality issues.
• Contribute to the shift from static dashboards to agentic data systems by building foundational data layers that AI agents query and reason over

Skills

Data engineering

ETL/ELT design

SQL

Data modeling

Tools

Redshift

S3

Glue

Lake Formation

Lambda

Athena

EMR

Kinesis

Fire Hose

IAM

Job description

Amazon Web Services, Inc. in Austin, TX is seeking an on-site Data Engineer to design, build, and operate scalable ETL/ELT pipelines that ingest product telemetry, usage events, and business data across the STT portfolio.

You will join a growing analytics team, work with BI engineers and scientists to shape a centralized data platform using AWS services, implement data models linking usage signals to business outcomes, and contribute to data quality and self-serve analytics for thousands of AWS