{"id":3392550,"url":"https://alion.io/job/amazon-data-engineer-ii-1-year-ftc-supply-chain-optimization-technologies-planning","title":"Data Engineer II (1 Year FTC), Supply Chain Optimization Technologies - Planning","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":78,"open_postings":4454,"ghost_share":0,"stale_share":0.888,"repost_share":0.001,"time_to_fill_p50_days":24,"computed_at":"2026-11-01T06:10:25Z"}},"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":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":75000,"max_usd":180000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":14},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Amazon S3","optional":true},{"name":"AWS","optional":true},{"name":"AWS Glue","optional":true},{"name":"AWS Lambda","optional":true},{"name":"IAM","optional":true}],"status":"live","first_seen_at":"2026-10-28T10:50:51Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-02T02:17:59Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"**This is a 1 Year FTC contract**\nAre you passionate about building data solutions that power decisions at massive scale? As a Data Engineer II at Amazon, you will design, build, and optimize data architectures that turn raw information into reliable, high-quality datasets used by analysts, scientists, and engineering teams. You will work across the full data lifecycle - from ingesting and transforming semi-structured data streams to creating logical data models that drive physical design and enable self-service analytics. This role offers the opportunity to solve complex data challenges, improve how teams discover and trust their data, and directly influence business outcomes through the systems you create.\nKey job responsibilities\n- Design and implement ETL workflows and data pipelines that extract, transform, and load data at scale, ensuring stability, performance, and efficient resource usage across distributed systems and cloud infrastructure.\n- Create and maintain logical and physical data models that accurately represent business requirements, enforce data integrity, and support downstream analytics and reporting needs.\n- Write clean, well-documented code using SQL and scripting languages to automate data processes, optimize query performance, and build tools for tracking data lineage and improving data quality.\n- Collaborate with analysts, scientists, and software engineers to understand data requirements, balance competing priorities, and deliver usable datasets that provide clear business value.\n- Participate in code reviews, design discussions, and operational excellence initiatives, contributing to continuous improvement of team data solutions while mentoring peers on system architecture and best practices.\nA day in the life\nYou will start your day reviewing pipeline health dashboards and resolving any data quality issues before they reach downstream consumers. From there, you might pair with a scientist to refine a data model, write and optimize SQL queries for a new reporting dataset, or evaluate a generative AI tool to accelerate a repetitive transformation task. Afternoons often include design reviews with your team, where you propose improvements to existing architectures or troubleshoot production incidents at their root cause.\nAbout the team\nOur team is focused on building reliable, scalable data infrastructure that empowers teams across Amazon to make faster, better-informed decisions. We value collaboration, technical curiosity, and a commitment to simplifying complex systems. As we continue to grow, you will have the opportunity to shape the tools and processes that define how data is managed and consumed. If you are excited about working in an inclusive environment where your ideas directly influence how we build for the future, we would love to hear from you.\nBasic qualifications\n- Experience in data engineering\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 opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.\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. 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