Why this role exists
Peak One works with one shared data model rather than many separate copies. Reports, AI suggestions and decisions are built on that data. If data is incomplete, duplicated or wrong, everything on top becomes unreliable. This role turns data quality and data flows into a solid, checkable foundation.
Your outcomes
- Documented data flows with clear lineage for every important field.
- Automated quality checks that surface errors early.
- Reliable data foundations for reporting and AI features.
- Privacy-aware rules for access, retention and deletion, developed together with others.
Your day and scope
Building and maintaining data models and pipelines, writing quality checks, finding root causes of data errors, clarifying requirements with Product, AI engineering and Revenue Operations and documenting definitions. Personal data only to the extent necessary and under clear rules.
Boundaries: You own data flows, data quality and analysable data foundations. Product features, AI applications and individual business reports are built together with the respective roles.
Your first 90 days
First 30 days
Understand the data model, data sources and known quality issues; name the most critical gaps.
By day 60
Deliver first automated quality checks and one documented pipeline for an important data area.
By day 90
Run a data foundation that Product and AI engineering trust, and have presented an improvement plan for the next areas.
What you bring
- Hands-on experience with data modelling and SQL.
- Experience building and running data pipelines.
- High standards for data quality and documentation.
- Basic understanding of data protection when handling personal data.
What you can learn with us
- Our specific tools and infrastructure.
- The business meaning of our data in detail.
When this role is less of a fit
You only want to build dashboards without caring about where data comes from and how good it is.
Compensation and conditions
We only commit to compensation, contract type, working hours and location once they are approved. We will tell you all of it concretely in the first call, before you invest time in further steps.
Your application process
Short application
Name, email and your answer to the role's entry question. CV optional.
First call
A personal conversation about the role, conditions and your questions. We cover compensation and location concretely here.
Work sample
An announced, time-boxed task with a synthetic dataset: find quality issues, propose a clean-up and write validation rules. No real data, no unpaid work for Peak Atlas. People assess approach, care and explanation.
Decision
A person decides, never an AI. You always get a response.
Your entry question
„The same company appears several times in Peak One with slightly different names. How do you proceed without accidentally merging different companies?“
Apply now