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

Nominate & Attend

Data Engineer, IN Data Engineering & Analytics

Amazon
London
1 week ago
Create job alert

Amazon IN Platform Development team is looking to hire a rock star Data/BI Engineer to build for pan Amazon India businesses.

Amazon India is at the core of hustle @ Amazon WW today and the team is charted with democratizing data access for the entire marketplace & add productivity. That translates to owning the processing of every Amazon India transaction, for which the team is organized to have dedicated business owners & processes for each focus area. The BI Engineer will play a key role in contributing to the success of each focus area, by partnering with respective business owners and leveraging data to identify areas of improvement & optimization. He / She will build deliverables like business process automation, payment behavior analysis, campaign analysis, fingertip metrics, failure prediction etc. that provide edge to business decision making AND can scale with growth. The role sits in the sweet spot between technology and business worlds AND provides opportunity for growth, high business impact and working with seasoned business leaders.

An ideal candidate will be someone with sound technical background in data domain – storage / processing / analytics, has solid business acumen and a strong automation / solution oriented thought process. Will be a self-starter who can start with a business problem and work backwards to conceive & devise best possible solution. Is a great communicator and at ease on partnering with business owners and other internal / external teams. Can explore newer technology options, if need be, and has a high sense of ownership over every deliverable by the team. Is constantly obsessed with customer delight & business impact / end result and ‘gets it done’ in business time.

Key job responsibilities

  • Design, implement and support an data infrastructure for analytics needs of large organization
  • Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies
  • Be enthusiastic about building deep domain knowledge about Amazon’s business.
  • Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.
  • Enjoy working closely with your peers in a group of very smart and talented engineers.
  • Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
  • Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency

    About the team
    India Data Engineering and Analytics (IDEA) team is central data engineering team for Amazon India. Our vision is to simplify and accelerate data driven decision making for Amazon India by providing cost effective, easy & timely access to high quality data. We achieve this by building UDAI (Unified Data & Analytics Infrastructure for Amazon India) which serves as a central data platform and provides data engineering infrastructure, ready to use datasets and self-service reporting capabilities. Our core responsibilities towards India marketplace include a) providing systems(infrastructure) & workflows that allow ingestion, storage, processing and querying of data b) building ready-to-use datasets for easy and faster access to the data c) automating standard business analysis / reporting/ dashboarding d) empowering business with self-service tools for deep dives & insights seeking.
    BASIC QUALIFICATIONS

    - 1+ years of data engineering experience
  • Experience with SQL
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
  • Experience with one or more scripting language (e.g., Python, KornShell)
    PREFERRED QUALIFICATIONS

    - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
  • Knowledge of AWS Infrastructure
  • Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model

    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.
    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

Lead Data Engineer...

Lead Data Engineer

Lead Data Engineer

Senior Data Engineer - KPMG Curve

Lead Data Engineer - KPMG Curve

Senior Data Engineer - KPMG Curve

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.

How to Present Data Science Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

The ability to communicate clearly is now just as important as knowing how to build a predictive model or fine-tune a neural network. In fact, many UK data science job interviews are now designed to test your ability to explain your work to non-technical audiences—not just your technical competence. Whether you’re applying for your first data science role or moving into a lead or consultancy position, this guide will show you how to structure your presentation, simplify technical content, design effective visuals, and confidently answer stakeholder questions.

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.