Senior Data Engineer, Specialist Technology Team (STT), Centralized Data & Analytics

AWS Specialist Technology Team (STT) is the connective tissue between AWS's deep technical specialists, field teams, and customers—delivering L300+ technical expertise, mechanisms, and products that accelerate customer success and drive frictionless AWS adoption at scale. Our mission spans two fronts: we are fundamentally transforming how thousands of field team members access specialist knowledge through AI-powered, on-demand expertise across 30+ technical domains, and we build and ship customer-facing engineered solutions that accelerate AWS service adoption across industries. Our portfolio spans AI-powered specialist knowledge systems (Specialist Agent, Knowledge Vault), hands-on engagement platforms (Workshop Studio), content quality and recommendation engines (Holmes), and go-to-market orchestration tools (Alchemy)—collectively enabling field teams to deliver high-quality technical engagements at scale. These products serve thousands of users across the AWS sales organization, generating rich signals about content effectiveness, engagement delivery, knowledge consumption, and field team productivity. We are seeking a Senior Data Engineer to join our newly formed centralized analytics team as one of the first Data Engineers on the team. This is a greenfield opportunity to build a data platform from the ground up—making foundational architectural decisions and directly influencing how an entire organization measures success and makes investment decisions. You will design, build, and operate scalable data pipelines that connect product telemetry, usage metrics, and business outcomes into a coherent, unified data ecosystem. Your focus will be squarely on engineering—building robust, scalable infrastructure and data models—while dedicated Business Intelligence Engineers on the team own the reporting, dashboarding, and stakeholder-facing analytics. This is not traditional reporting—you will be building the data backbone that powers intelligent, agent-driven analytics experiences (MCP tools, agentic retrieval systems) enabling stakeholders to intuitively access and consume data within their day-to-day workflows. The data you engineer will inform executive reviews, drive product strategy, and power the next generation of self-service analytics tools used by thousands of AWS field team members. Key job 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 (e.g., content effectiveness to field engagement to pipeline progression to revenue impact) - Lead the development of data infrastructure supporting AI/ML pipelines and agentic systems, including MCP tools and natural-language data access layers, contributing to the evolution from static dashboards toward agentic data systems by building the foundational data layers that AI agents query and reason over - Establish and enforce data governance best practices including data contracts, lineage tracking, catalog metadata, data quality frameworks with automated monitoring, alerting, and validation to ensure accuracy, consistency, compliance with security and privacy regulations, and trust across the organization - Build self-service data products with clear SLAs, documentation, and governance that reduce ad-hoc request burden and