Description Are you passionate about solving complex data challenges at scale? Do you want to build innovative data solutions that power talent decisions for 1.5+ million Amazonians? Role Overview: Join AMX SIERRA's engineering organization, where you'll collaborate with Data Engineers, Software Developers, UX designers, Business Intelligence Engineers, and Data Scientists to build enterprise-scale data products and services that impact Amazon's global workforce. Key job responsibilities As a Data Engineer II, you should bring: • Expert knowledge in data lake fundamentals (storage, compute) • Deep understanding of data processing stacks (Spark, EMR) • Mastery of enterprise-level data lake/mesh solutions using AWS stack • Expertise in designing, creating, and managing large datasets • Experience with ML feature engineering and AI data pipelines • Ability to build efficient, flexible, and scalable ETL solutions • Enthusiasm for learning and implementing new technologies • Comfort with complex, evolving business contexts Key Responsibilities: • Design and implement secure, scalable data platforms • Architect and maintain end-to-end data infrastructure • Build and optimize data processing and ML feature pipelines • Develop and maintain AI knowledge bases • Drive data strategy and technical roadmap development • Interface with multiple teams to integrate diverse data sources • Implement complex ETL pipelines and BI solutions • Ensure data quality for ML model predictions • Foster team self-service capabilities and knowledge sharing A day in the life On any given day, you might be: • Designing a new data pipeline to capture employee lifecycle events • Optimizing performance of our ML feature processing systems • Collaborating with data scientists to enhance our AI knowledge bases • Troubleshooting data quality issues affecting business insights • Participating in design reviews for new data architecture Beyond the regular pipeline work, you'll have opportunities to: • Lead technical initiatives to improve our data infrastructure • Mentor other engineers on data engineering best practices • Pilot new technologies to solve emerging challenges • Shape how we approach data quality and governance You'll interact regularly with: • Data scientists building prediction models • Analytics teams using your data pipelines • Product teams developing AI applications • Business partners defining requirements This role combines hands-on technical work with strategic thinking - one day you might be deep in code optimizing a pipeline, the next you could be architecting a new feature repository solution. About the team About the Team: We build data solutions that power Amazon's talent analytics and AI-driven HR tools. Our customers range from HR teams making promotion decisions to AI systems providing employee guidance - all relying on our data infrastructure to make informed decisions. What we do: • Power analytics that influence workforce decisions • Build data foundations for AI-powered HR applications • Drive data quality and governance standards Your impact: You'll work directly with: • Data scientists building next-gen talent prediction models • Analytics teams needing reliable, high-quality data • Product teams developing AI-powered HR solutions • Business partners defining critical metrics Our culture emphasizes: • Collaborative problem-solving • Innovation with practical implementation • Knowledge sharing and mentorship • Data-driven decision making We're looking for someone who shares our passion for solving complex data challenges while maintaining high standards for reliability and quality. Basic Qualifications - 3+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with SQL - Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS 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) - Experience building large-scale, high-throughput, 24x7 data systems 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. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.