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 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
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
About the team You will be joining 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—you will be one of the first two Data Engineers on the team, working alongside Business Intelligence Engineers, a Senior BD, an Applied Scientist, and a TPM. You will make foundational architectural decisions that define how the platform will be built, scaled, and operate for years to come. The pace of innovation is high, the problems are ambiguous, and the impact is measured across thousands of field team members and the customers they serve. This role offers the opportunity to shape foundational architecture decisions and influence how an entire organization consumes and acts on data.
About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
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Basic 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
Preferred Qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 145,300.00 - 196,600.00 USD annually USA, TX, Austin - 132,100.00 - 178,800.00 USD annually USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually