You'll be the go-to Databricks expert on the team. You'll have important role in the migration from the legacy stack while designing and building the new platform in parallel - and "in parallel" is doing real work in that sentence.
You will work on:
Design & build the new streaming platform (Kafka → Databricks with Declarative Pipelines)
Migrate existing batch workflows from Airflow + Docker + on‑prem Databricks to cloud‑native architecture
Keep the current platform stable while improving its reliability, performance and operability
Architect the serving layer
Govern data properly - Unity Catalog, lineage, access control, data quality - not as an afterthought
Enable sharing across organization with Polaris and Iceberg
Collaborate with data scientists, ML engineers, and business teams across regions
Use AI tools daily - we use GitHub Copilot and internal homemade assistants/agents we build on our own within a team; we expect you to help the team get real value from them
You will thrive here if you:
Know Databricks deeply - Unity Catalog, Delta Live Tables / Declarative Pipelines, Workflows, Bundles - not just "used it on a project"
Have streaming experience - Kafka, event-driven architectures, late data handling, exactly-once semantics
Have worked in consulting or client-facing roles - you can communicate with business stakeholders and stay focused on outcomes
Are comfortable with imperfect systems - the legacy stack has rough edges; you'll sand them down while building something better
Don't need the work to be glamorous - some weeks it's streaming architecture, some weeks it's debugging a broken Airflow DAG
Are genuinely curious about AI tooling - Copilot/LLMs/agents are part of your workflow
What you bring:
3-5+ years of experience in data engineering (the specific tech stack is flexible - we value your way of thinking and problem‑solving above tools)
Strong consulting mindset or experience working closely with business stakeholders, with the ability to ask the right questions, challenge assumptions and translate business needs into technical solutions
End‑to‑end ownership approach - from designing and building solutions to monitoring, improving and maintaining them
Excellent communication and collaboration skills, enabling you to work effectively across teams and influence decisions
Degree in Computer Science/Engineering or equivalent hands‑on experience
Experience with Databricks, Spark and streaming technologies (e.g., Kafka) - a strong plus
Proficiency in English at a minimum B2 level , spoken and written
Tech you will touch:
New stack: Kafka
Databricks Declarative Pipelines
Unity Catalog
Apache Iceberg
Polaris Catalog
incremental materialized views
AI developer tooling
Legacy stack: Apache Airflow
Docker
on‑prem compute/servers
existing Databricks jobs and batch ETL
Benefits
By joining our team, you become a part of the people-centric work environment of a Danish company. We offer you a competitive salary, permanentFlexible schedule
Additional Information
We are seeking a Senior Data Engineer position based in our Poznań location to join the Data Science & Engineering team.
Ready to help build a better future for generations to come?
In an ever-changing world, we owe it to ourselves and our future generations to live life responsibly. At ROCKWOOL, we work with dedication to enrich modern living through our innovative stone wool solutions.
Join us and make a meaningful difference!
Your future team:
You will join our Data Science & Engineering Team , a group of 12 skilled professionals including the Team Leader. The team combines strong expertise in data engineering, analytics, and machine learning, and is structured into several project‑focused sub‑teams working across a variety of business areas.
What we are building:
Our data platform is already there in cloud, already in Databricks. But we're not here to maintain the status quo - we're rebuilding it from the ground up to jump into exciting world of real-time data and streaming.
We will migrate from a batch-oriented Airflow + Databricks to a streaming-first architecture: Kafka, Databricks with new cool features like Declarative Pipelines, Unity Catalog, Apache Iceberg / Polaris Catalog, and new serving layer, which you will help us to select.
This is a greenfield build inside a global company - real budget, real data, real stakes. No startup chaos, but real room to make meaningful architectural decisions.
Rockwoolgroup · Poznań