{"id":2829674,"url":"https://alion.io/job/amazon-data-engineer-ii-intl-seller-services","title":"Data Engineer II, Intl. Seller Services","company":{"id":19,"name":"Amazon","domain":"amazon.com","url":"https://alion.io/company/amazon","size_band":"1-10","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":83,"open_postings":4347,"ghost_share":0,"stale_share":0.886,"repost_share":0.001,"time_to_fill_p50_days":17,"computed_at":"2026-10-21T05:46:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Seattle, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":132100,"max":178800,"currency":"USD","period":"year","gross":null,"usd_annual":178800},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AWS","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Amazon S3","optional":true},{"name":"AWS Glue","optional":true},{"name":"AWS Lambda","optional":true},{"name":"IAM","optional":true}],"status":"closed","first_seen_at":"2026-10-18T00:00:00Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-20T18:44:07Z","board_verified":false,"closed_at":"2026-10-20T18:44:07Z","days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Come be part of Amazon’s International Seller Services (ISS) Central Analytics Data Engineering team, where we tackle modern data challenges by combining traditional engineering practices with transformative analytics and Generative AI.\nISS is seeking a highly motivated, experienced Data Engineer to help design and build the next generation of Data and ML infrastructure to power GenAI applications.\nWe are a team of Data Engineers working closely with Applied Scientists, Data Scientists, and Economists-turning machine learning, deep learning, and AI research into scalable products that delight our customers worldwide.\nISS is seeking a highly motivated, experienced Data Engineer to help design and build the next generation of Data and ML infrastructure to power GenAI applications.\nKey job responsibilities\nAs a Data Engineer, you will provide technical leadership, lead data engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective.\nYou are passionate about working with huge datasets and have experience with the organization and curation of data for analytics. You have a strategic and long term view on architecting advanced data eco systems.\nYou are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.\nDesign, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.\nImplement data ingestion routines using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.\nGather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.\nCollaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation\nIdentify opportunities in existing data solutions for improvements\nBasic qualifications\n- 3+ years of data engineering experience\n- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience\n- 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience\n- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience\n- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience\n- 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience\n- 3+ years of in the job offered or a related occupation experience\n- 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience\n- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field\n- Experience with data modeling, warehousing and building ETL pipelines\nPreferred qualifications\n- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions\n- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)\nAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.\nOur 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.\nThe 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. 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