Data Engineer – Build a Scalable AWS Data Platform

Amazon Web Services (AWS); Austin (TX); On-site; USD 132,100 - 178,800; Full time

Job summary

Amazon Web Services, Inc. in Austin, TX is seeking a Data Engineer to join a greenfield analytics initiative.

You will design, build, and operate scalable data pipelines, ingesting telemetry, usage, and business data across the STT portfolio to power self-serve analytics and AI-enabled workflows for thousands of field teams. You will partner with SDEs and Applied Scientists to craft well-modeled data foundations using AWS-native services (Redshift, S3, Glue, Lake Formation, Lambda).

Qualifications

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

Responsibilities

• Design, build, and operate scalable ETL/ELT pipelines that ingest product telemetry, usage events, and business outcome data from multiple heterogeneous sources across the STT product portfolio.
• Architect and implement a centralized data platform using AWS-native technologies (Redshift, S3, Glue, Lake Formation, Lambda, Athena) that serves as the single source of truth for organizational analytics.
• Build and maintain data models that connect product usage signals to business outcomes (e.g., content effectiveness -> field engagement -> pipeline progression -> revenue impact).
• Develop data infrastructure supporting AI/ML pipelines and agentic systems, including MCP tools and natural-language data access layers.
• Implement data quality frameworks with automated monitoring, alerting, and validation to ensure accuracy and reliability as the platform scales.
• Build self-service data products with clear SLAs, documentation, and governance that reduce ad-hoc request burden and empower stakeholders to answer their own questions.
• Partner 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—owning on-call, monitoring pipeline health, and proactively resolving data freshness or quality issues before they impact consumers.
• Contribute to the evolution from static dashboards toward agentic data systems by building the foundational data layers that AI agents query and reason over

Skills

Data engineering

SQL

Data modeling

ETL/ELT pipelines

AWS data services

Tools

Redshift

S3

Glue

Lake Formation

Lambda

Athena

EMR

Kinesis

IAM

Job description

Amazon Web Services, Inc. in Austin, TX is seeking a Data Engineer to join a greenfield analytics initiative.

You will design, build, and operate scalable data pipelines, ingesting telemetry, usage, and business data across the STT portfolio to power self-serve analytics and AI-enabled workflows for thousands of field teams. You will partner with SDEs and Applied Scientists to craft well-modeled data foundations using AWS-native services (Redshift, S3, Glue, Lake Formation, Lambda).