BI / Reporting Analyst (all genders)
stark · Munich
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About the role
About Us
STARK is a new kind of defence technology company revolutionising the way autonomous systems are deployed across multiple domains. We design, develop, and manufacture high-performance unmanned systems that are software-defined, mass-scalable, and cost-effective — providing operators with a decisive edge in contested environments.
We are focused on delivering deployable, high-performance systems — not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe, today.
About the team
Your mission
As OPA Lead, you own the quantitative backbone of operations. You design and run the S&OP process, define the KPI framework, and produce WBR/MBR data packs that give leadership a reliable, accurate picture of the business. You build the planning rhythm from scratch and develop the team beneath you.Responsibilities
Audit existing data flows across ERP, MES, and PLM - understand what exists, where it lives, and how it reaches reporting outputs
Design a structured data storage and pipeline architecture - defining sources of truth, data models, and refresh cadences
Build and maintain reliable data warehouse structure and pipelines to replace manual CSV exports and point-to-point connections
Own data quality: define checks, document known issues, and ensure stakeholders can trust what they see
Document data models, pipeline logic, and reporting definitions - no tribal knowledge dependencies
Partner with the Operations Planning and Analytics Lead to translate operational questions into well-structured data products
Qualifications
3–5 years in data engineering, analytics engineering, or BI roles
SQL (strong) - complex queries, performance optimisation, views and models
ETL/ELT pipeline design and maintenance
Data modelling — understanding of dimensional and relational models
Comfortable with ambiguity in a build-from-scratch environment — no clean data model to inherit
BSc in Computer Science, Data Science, Business Informatics, or equivalent
Nice to have
Python or dbt for pipeline automation and data transformation
ERP and/or MES system familiarity — understanding how operational data is structured at source
Experience connecting heterogeneous operational systems (ERP, MES, PLM, or similar)
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