Senior Data Analyst; m​/f​/d

Job Description

Shopware is a leading ecommerce system that enables companies worldwide to scale quickly and efficiently in digital commerce. As a trendsetting open source solution, Shopware is already used by some of the largest European brands, retailers and manufacturers in the B2C and B2B industries.

Shopware is a leading ecommerce system that enables companies worldwide to scale quickly and efficiently in digital commerce. As a trendsetting open source solution, Shopware is already used by some of the largest European brands, retailers and manufacturers in the B2C and B2B industries.

ARR, revenue, GMV. These are the numbers our management team and our shareholders steer by. Someone has to own what they actually mean, decide when the technical definition needs to change, implement that change in our data warehouse, and make sure the people who use those numbers can explain and defend them themselves.

That is this role. It is not a reporting role that fills requests. It is the role that owns the analytical foundation under our business-critical KPIs
, from the SQL logic in the data warehouse to the technical definition Finance and management rely on when someone asks why last month's number moved.

This position can be filled on-site
, hybrid
, but also full-remote within Germany or specific European countries where we are registered. Your work location will be agreed upon in advance and forms the basis of your employment contract.

These are your tasks:

• KPI ownership:
  You own the technical definitions and the logic behind our business-critical KPIs, ARR and revenue first among them. Not only maintaining them, but judging when the technical definition needs to change, escalating that change through our governance guardrails and approval process, implementing it, and standing behind the result, including when it is challenged under audit or external scrutiny. This includes the communication: explaining definitions and changes proactively and understandably, from operational teams up to management level.
• Technical craft and the data landscape:
  You build, debug and QA your own analytical logic. Strong SQL means you assemble the data you need yourself instead of queueing for it. You bring a real end-to-end model of how data moves from source systems through the data warehouse into reporting. Enough to tell a data problem from a process problem from a definition problem, to know when something has to be fixed at the source rather than patched in a report, and to work through a substantial, live backlog with the judgment to prioritize independently from day one, without close supervision.
  
  You will not own our pipelines or the platform; our data engineers do that and you work with them closely.
• Enabling instead of delivering:
  You shape definitions, models and reporting so that stakeholders can answer their own follow-up questions instead of coming back to BI for each one. Concretely for Finance: you build the data, tooling and transparency that let them take full ownership of the topics that are rightly theirs, such as month-end close and ARR corrections. BI owns the definition and the technical implementation;
  Finance owns the process and the number. The target is a process Finance runs itself.
• Governance as change management:
  Together with the Head of BI you set up and land a governance framework for business-critical KPIs: what ownership means on the business side and on the BI side, how definitions are documented, kept current and kept audit-ready, and how changes are reviewed, decided and communicated. The hard part here is adoption, not documentation, and you will have the mandate and the leadership backing to drive it.
• Knowledge transfer:
  You share workflows, logic and ways of…