National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Engineer II, Data Engineering - Case Management

Amazon
London
1 week ago
Create job alert

Would you like to work on one of the world's largest transactional distributed systems? How about working with customers and peers from the entire range of Amazon's business on cool new features? Whether you're passionate about building highly scalable and reliable systems or a software developer who likes to solve business problems, Selling Partner Services (SPS) is the place for you. Our team is responsible for Case Management System. We are looking for data engineers who thrive on complex problems and solve for operating complex and mission critical systems under high loads. Our systems manage case resolution systems with hundreds of millions of requests, and respond to millions of service requests. We have great data engineering and science opportunities. We are aimed to provide customizable and LLM based solution to our clients. Do you think you are up for this challenge? Or would you like to learn more and stretch your skills and career? The successful candidate is expected to contribute to all parts of the data engineering and deployment lifecycle, including design, development, documentation, testing and maintenance. They must possess good verbal and written communication skills, be self-driven and deliver high quality results in a fast paced environment. You will thrive in our collaborative environment, working alongside accomplished engineers who value teamwork and technical excellence. We're looking for experienced technical leaders.

Key job responsibilities

  1. Design/implement automation and manage our massive data infrastructure to scale for the analytics needs of case management.

    2. Build solutions to achieve BAA(Best At Amazon) standards for system efficiency, IMR efficiency, data availability, consistency & compliance.

    3. Enable efficient data exploration, experimentation of large datasets on our data platform and implement data access control mechanisms for stand-alone datasets

    4. Design and implement scalable and cost effective data infrastructure to enable Non-IN(Emerging Marketplaces and WW) use cases on our data platform

    5. Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL, Amazon and AWS big data technologies

    6. Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.

    7. Drive operational excellence strongly within the team and build automation and mechanisms to reduce operations

    8. Enjoy working closely with your peers in a group of very smart and talented engineers.
    BASIC QUALIFICATIONS

    - 3+ years of data engineering experience
  • Experience with SQL
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
  • Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
    PREFERRED QUALIFICATIONS

    - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
  • Experience building large-scale, high-throughput, 24x7 data systems
  • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
  • Experience providing technical leadership and mentoring other engineers for best practices on data engineering

    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 visithttps://amazon.jobs/content/en/how-we-hire/accommodationsfor more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
    Posted:

    December 16, 2024 (Updated about 5 hours ago)
    Posted:

    May 24, 2025 (Updated about 11 hours ago)
    Posted:

    May 24, 2025 (Updated about 11 hours ago)
    Posted:

    May 24, 2025 (Updated about 13 hours ago)
    Posted:

    March 1, 2025 (Updated about 19 hours ago)
    Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

    #J-18808-Ljbffr

Related Jobs

View all jobs

Software Engineer II - Data Engineer, Python, SQL - Associate

Software Engineer II - Data Engineer, Python, SQL - Associate

Data Engineer-II, Fintech

Software Engineer II - Data Engineer, Python, SQL - Associate

Data Engineer II

Data Engineer II, AWS Finance Technology

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.