Data Engineer - Parental Leave Cover

OOONO; København; Sur place; DKK 800 000 - 1 100 000; Plein temps

Avantages offerts par ce poste

Table tennis

Foosball

Monthly social events

Go-karting / festivals

Résumé du poste

OOONO is seeking a Data Engineer to cover parental leave in the Data & AI team. You will keep a live AWS data platform healthy while making it better, enabling data scientists to push their work into production and handing back well-documented work for a smooth transition.

You’ll be the engineering link between data scientists, data engineers, and software developers, contributing to a small team where your work makes a visible difference. This fixed-term role runs until end-March 2027.

Qualifications

• Has run AWS data services in production (S3, Glue, Athena, Lambda and SQS).
• Knows how to debug a failed job or a full dead-letter queue.
• Has changed an existing multi-stack AWS CDK app in Python, and reads the cdk diff before deploying, not after.
• Writes strong, production-quality, tested Python and solid SQL for analytics and transformation.
• Has written and tuned PySpark batch jobs on real data volumes.

Responsabilités

• Take data scientists' workloads to production, focusing on data pipelines and soon ML models.
• Collaborate with software developers to align data contracts and APIs between product and platform.
• Keep the production platform healthy by monitoring jobs, debugging issues, and performing backfills.
• Modify the AWS CDK app via pull requests, code review, and per-environment deployments.
• Maintain documentation and hand over a clearly documented state at the end.

Connaissances

Python

PySpark

SQL

AWS production

Data contracts

Monitoring & debugging

Outils

AWS CDK

S3

Glue

Athena

Lambda

SQS

Description du poste

Some data engineers want to build a platform from scratch. We’re looking for one who’d rather take the keys to a running one. Our AWS data platform is live, busy and in good shape, and we need someone who can keep it that way while making it even better.

We’re looking for a Data Engineer to cover a parental leave in our Data & AI team, from as soon as possible until end of March 2027. It’s a fixed-term role, but it’s not a caretaker job. You’ll keep the production platform healthy, help our data scientists get their work into production, and hand it all back so well documented that our colleague can pick up right where you left off.

You’d join our Data & AI team, reporting to our Head of Data & AI. Your closest teammates are our data engineer, our data scientists, who build the algorithms behind the warnings our drivers rely on, and our software developers, who build the product the data flows through. You’ll be the engineering link between the two. It’s a team small enough that your work makes a visible difference, and where help and someone to spar with are never far away.

What you’ll be doing

• Work alongside our data scientists to take their workloads to production. Today those are mostly data pipelines, with ML models next in line. That means packaging, infrastructure, scheduling and monitoring, and keeping things running long after launch day.
• Work closely with our software developers to align data contracts and APIs, so data flows cleanly between the product and the platform.
• Keep the production platform healthy: monitor jobs, debug failed Glue and Lambda runs, work through dead-letter queues, and run backfills and redrives.
• Change our AWS CDK app through pull requests, code review and per-environment deployments.
• Work with coding agents day to day, maintain our shared agent skills and keep the documentation current.
• Hand back a documented state at the end: what was deployed, what changed, what’s still open and what to watch.

We imagine you’re someone who

• Has run AWS data services in production (S3, Glue, Athena, Lambda and SQS), and knows how to debug a failed job or a full dead-letter queue.
• Has changed an existing multi-stack AWS CDK app in Python, and reads the cdk diff before deploying, not after.
• Writes strong, production-quality, tested Python and solid SQL for analytics and transformation.
• Has written and tuned PySpark batch jobs on real data volumes.
• Works well across disciplines: has turned data scientists’ prototype code into reliable production pipelines, works day to day with software developers, and is comfortable being the engineering link between the two.
• Works productively with coding agents, reviews their output critically and pushes back when it’s wrong or unsafe.
• Writes documentation that both colleagues and agents can use, so the next person can pick up the work without you in the room.

Even better if you’ve worked with

• Cloud data warehouses on a lakehouse architecture, such as Snowflake, Redshift or Databricks reading from a lakehouse
• Apache Iceberg or other lakehouse table formats, ideally S3 Tables, including MERGE-based upserts and schema management
• Dimensional data modelling: facts, dimensions and aggregates, including slowly changing dimensions
• Data contracts and data quality: schema-as-code and operating data quality checks
• Event-driven architecture: cross-account EventBridge, replay and idempotency
• Geospatial processing (H3, pyproj or similar)

How is it working at OOONO?

We’re glad we asked. It’s a nice working place. As in nice-nice. We have a relaxed, informal atmosphere and a flat hierarchy. Whenever you need a break from your important work stuff, you can get beaten at table tennis or foosball, or just make small talk about the weather by the coffee machine. We have monthly social events, where we do anything from go-karting to going to festivals.

And when we’re not social? Then we’re pretty damn ambitious. We don’t like conservative targets or linear growth. We’re all about the extraordinary. That has made OOONO one of the fastest-growing tech scaleups, and surprise-surprise: we have no plans of slowing down.

The practical stuff

• Duration: Fixed-term parental leave cover until 5 March 2027