Sr. Data Engineer, Amazon PeopleInsights eXperience (APIX)

Are you passionate about building scalable data infrastructure that powers critical business decisions? Do you thrive on solving complex data architecture challenges while mentoring engineers and driving technical excellence? If so, join the Amazon People Insights & Experience (APIX) team as a Senior Data Engineer!We're transforming Amazon's fragmented people-data ecosystem into a centralized, AI-ready platform through the PXT Data Strategy—a multi-year program consolidating 20 data lakes with 13,000+ data sources into a unified Central Lakehouse serving 440+ data teams. As a Senior Data Engineer, you'll be instrumental in building the data infrastructure that enables self-service analytics, AI-powered insights, and data governance at massive scale.This is a hands-on technical leadership position where you will own team-level data architecture for flagship initiatives including the Central Lakehouse (achieving 100% Golden Dataset discoverability), Amazon Cortex (an intelligent data abstraction platform), and Clarity Metrics Marketplace (CMM)—reducing dataset onboarding time from 5-6 weeks to under 7 days. You'll architect solutions that serve 16,000+ HR professionals, operations leaders, and people managers across Amazon, directly impacting how the company makes data-driven workforce decisions.We're looking for a top data engineer with deep expertise in distributed systems, data lake architectures, and a proven track record of delivering large-scale data solutions. You should excel at technical leadership, strategic thinking, and have genuine passion for building data infrastructure that scales to support hundreds of teams building metrics in parallel while maintaining Amazon's highest privacy and security standards.Key job responsibilitiesOwn Team Data Architecture & Drive Technical Excellence- Take ownership of team data architecture with system-wide perspective, anticipating data access patterns and proactively removing bottlenecks across the Central Lakehouse, Cortex, and CMM platforms- Design and deliver exemplary, large-scale data solutions that are secure, maintainable, scalable, and extensible—enabling others to easily contribute and build upon your work- Lead architectural improvements that simplify complex data systems, addressing deficiencies where your team's architecture bottlenecks other teams across PXT's 20 data lakes- Make appropriate architectural trade-offs (build vs. buy, tiered storage strategies, data abstraction patterns) balancing short-term technology needs with long-term business requirements for Amazon's people data ecosystem- Solve Ambiguous Problems & Lead Technical Strategy- Work efficiently with limited guidance in ambiguous problem areas—where business problems are defined but technical strategies for Golden Dataset onboarding, metadata enrichment, and AI contextualization are not- Lead identification and resolution of complex data engineering challenges including data duplication across 264 redundant warehouses, inconsistent metric definitions, and governance gaps across federated data lakes- Influence team technical and business strategy for PXT Data Strategy workstreams, bringing perspective and context for current and future technology choices in AWS-first data platform adoption- Build consensus when confronted with discordant views on data architecture approaches, demonstrating judgment on when to leverage existing solutions versus building new capabilities- Deliver High-Impact Data Solutions at Amazon Scale- Design and implement scalable data pipelines, ETL processes, and data abstraction layers supporting the Central Lakehouse (1,754+ Golden Datasets), Cortex Data Plane APIs, and self-service CMM capabilities- Architect solutions handling high volumes of people data across 17,000+ applications, optimizing for data quality, availability, latency, security, performance, and integrity- Reduce manual data preparation effort by 60-80% through intelligent data vending, contextualized metadata, and automated dataset onboarding workflows- Deliver data infrastructure supporting AI-powered insights (Clarity Assist, Quick Suite integration) with >90% query accuracy and <7 day metric creation timelines- Drive Engineering Best Practices & Governance- Set and enforce standards for data discovery, naming conventions, operational excellence, data security, and code quality across PXT data engineering teams- Lead implementation of systematic governance through integration with FPDS primitives (DISAPERE, Maple, UBX), enabling policy-driven data classification, automated depersonalization, and cell-level access control- Collaborate with AWS BDT, Security, and FPDS teams to influence roadmaps for SageMaker Unified Studio (SMUS), Andes External Tables, and Quick Suite integration—addressing 95+ identified feature gaps- Ensure all data solutions comply with Amazon's privacy standards, GDPR/DSAR requirements, and Red certification processes for sensitive people data- Mentor Engineers & Elevate Team Capabilities- Actively mentor and coach data engineers and analysts across the organization, improving technical knowledge of distributed systems, data lake architectures, and AWS data services- Provide technical assessments and guidance for DE II and DE III promotion candidates, helping team members grow their careers- Lead design reviews for your team's data architecture and actively participate in design reviews of related software and data systems across PXT- Demonstrate technical influence over 1-2 teams through collaborative development efforts and increasing productivity through data engineering best practices- Stay Current with Evolving Data Technologies- Master the constantly evolving AWS data toolkit including Andes, Athena, Glue, Redshift, SageMaker Unified Studio, and Quick Suite—adopting AWS-first approaches while retiring bespoke solutions- Evaluate and integrate emerging technologies for data lake management, GenAI contextualization (Model Context Protocols, vector embeddings), and serverless data engineering patterns- Pioneer privacy-first architecture patterns and AI-ready data infrastructure that positions PXT as AWS QuickSight's #1 customer and establishes foundations for external AWS product offeringsAbout the teamMeet the behind the scenes team that enables our Operations and Human Resource Leaders to make informed decisions. The Amazon Clarity team builds reporting and analytics tools for our teams that fulfill customer promise every day. Whether it is Fulfillment Center team that delivers your Prime order in two days, our Amazon Locker team that lets you pick up your package anytime that is convenient for you, our Prime Now team getting you lunch in under an hour, or one of many more, the PeopleInsight group is there providing people metrics along the employee life-cycle for our global operations businesses. In addition to standard reporting, we leverage predictive analytics using ML to help our leaders focus their efforts in ways that will engage, retain and grow their associates.Basic qualifications- 5+ 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 practicesPreferred qualification - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR- Experience operating large data warehousesAmazon 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 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 .USA, WA, Seattle - 154,600.00 - 209,100.00 USD annually