Data Engineer I

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

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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.