AmazonPosted 1w ago

Data Engineer I, Data Technology and Products

Data Engineer I, Data Technology and Products at Amazon scores 65 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

ES, B, Barcelonajuniorfull-time

AI in this role

Build and maintain data foundations, lakehouse architecture, and agent-friendly data services powering AI and automation across operations.

awsredshifts3lambdapythonsql

ai-agentsdata-engineeringetlautomationcloud-computingdata-modeling

Are you passionate about data? Does the prospect of building the data foundation that every AI tool in Amazon Operations stands on excite you? Do you want to participate on data services that both people and agents can trust?

We are looking for a Data Engineer to contribute to the data foundations that power reporting, automation and AI across International Operations.

You will work with the team that owns data services end to end: gathering the requirements, desiigning, building, productionalizing and owning the service and cost. You will work in a lakehouse on AWS, with Redshift, S3, lambdas and you will own services that analysts, scientists and AI agents consume without asking you first. You strive for simplicity and automate what others would repeat. You treat data as a product with owners, contracts and an SLA, not as a scripted pipeline that solved an isolated business problem.

The position is based in Spain, with Barcelona preferred and Madrid considered. You will report to a Data Engineering Manager and work inside a delivery organization of engineers and analysts spread across Europe. The ideal candidate is comfortable in a fast moving environment, is a creative and analytical problem solver, and wants to build things that outlive the request that started them.

Key job responsibilities
- Build, evolve and support data products meant to be reused, not delivered once. Those include SLA contracts, service and cost telemetry, cost expectations and quality controls.
- Make everything self-healing and idempotent.
- Create services agent-friendly.
- Automate your own operational load.

A day in the life
You start by checking the health of the data services you own: SLA, quality checks, and cost. Anything red gets triaged first.

Then you move to build work. You are typically carrying one or two main projects at a time with a senior Data Engineer to support you. You write mainly Python and SQL, you review a teammate's pull request, and you use AI assistance to move faster on the mechanical parts while you manually deliver what should be specially curated.

You spend part of the week with your customers. You understand what problem they try to solve and agree on the right solution of the portfolio. This might mean using an existing solution, expaning an existing one or the opportuity to create a new one.

You will be trusted with real ownership early. You will also have senior engineers to design with, so you are never guessing alone on an architecture decision.

About the team
We are the data and analytics organisation inside GSARC, which brings together Product Compliance, Analytics and AI for Amazon's International Operations and Global Operations Services. Our customers span first mile, middle mile and last mile, plus the end to end planning and compliance teams behind them.

We are a distributed team with people in Barcelona, Madrid, London, Luxembourg and Munich, and we work daily with partner teams in North America and Asia. English is our working language.

Basic qualifications

- Experience in data engineering
- 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)
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

Preferred qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR

Amazon 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.

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.

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Skills and AI tools this role asks for

AI AgentsData EngineeringEtlAutomationCloud ComputingData ModelingAwsRedshift

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where automation was part of your work. What did you do?
Tell me about a project where cloud computing was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Agents, Data Engineering, Etl, Automation, and Cloud Computing. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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