Senior Data Engineer, Greenfield Data Platform

Amazon; Austin (TX); On-site; USD 155,000 - 209,000; Full time

Job summary

Amazon AWS, Senior Data Engineer in the STT group, is a greenfield role building a centralized analytics data platform. You will design scalable ETL/ELT pipelines ingesting telemetry, usage, and business data from diverse sources, using AWS-native tools to power agentic analytics for thousands of AWS field users.

You will lead data infrastructure for AI/ML pipelines, promote governance, and mentor junior engineers while influencing architecture and product decisions at scale.

Qualifications

• 7+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with SQL.
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS.
• Experience mentoring team members on best practices.

Responsibilities

• Architect and own the end to end data platform strategy for the STT product portfolio, designing scalable ETL/ELT pipelines that ingest product telemetry, usage events, and business outcome data from multiple heterogeneous sources using AWS-native technologies (Redshift, S3, Glue, Lake Formation, Lambda, Athena, MWAA, EMR, Data Zone)
• Define and drive the next generation data architecture for the organization improving scale, quality, and performance while establishing the technical vision and roadmap that aligns data infrastructure investments with business priorities
• Design and implement a centralized data platform serving as the single source of truth for organizational analytics, building and maintaining data models that connect product usage signals to business outcomes
• Lead the development of data infrastructure supporting AI/ML pipelines and agentic systems, including MCP tools and natural-language data access layers
• Establish and enforce data governance best practices including data contracts, lineage tracking, catalog metadata, data quality frameworks with automated monitoring, alerting, and validation
• Build self-service data products with clear SLAs, documentation, and governance that reduce ad-hoc request burden
• Partner with and provide technical guidance to Applied Scientists, SDE teams, and data consumers to provide clean, well modeled data for agent evaluation frameworks, retrieval quality measurement, content effectiveness scoring, and capacity simulations
• Improve existing solutions by identifying and driving cross team technical improvements, influencing engineering best practices, and raising the bar on data engineering standards across the organization
• Operate with a high bar for operational excellence owning on call, monitoring pipeline health, proactively resolving data freshness or quality issues before they impact consumers, and mentoring junior engineers on operational rigor
• Provide technical leadership and mentorship to data engineers on the team, setting technical direction, conducting design reviews, and elevating the team's overall engineering capabilities

Skills

Data engineering

Data modeling

ETL pipelines

SQL

Python/Java/Scala/NodeJS

Mentoring

Tools

Hadoop

Hive

Spark

EMR

Data Warehouses

Job description

Amazon AWS, Senior Data Engineer in the STT group, is a greenfield role building a centralized analytics data platform. You will design scalable ETL/ELT pipelines ingesting telemetry, usage, and business data from diverse sources, using AWS-native tools to power agentic analytics for thousands of AWS field users.

You will lead data infrastructure for AI/ML pipelines, promote governance, and mentor junior engineers while influencing architecture and product decisions at scale.