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
The Operations Excellence team sits within the COO organization and serves as a strategic partner to managers, team leads, and colleagues across Stark. By delivering data-driven insights, leading critical projects, and driving continuous process improvement, we help the organization operate more efficiently, scale effectively, and achieve its goals faster.
As an individual contributor, you will take end-to-end ownership of complex initiatives with significant business impact. Working closely with cross-functional stakeholders, you will have the opportunity to influence key decisions, shape core operating processes, and contribute directly to the success of one of Europe’s fastest-growing unicorns.
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
BSc in Computer Science, Data Science, Business Informatics, or equivalent
3–5 years in data engineering, analytics engineering, or BI roles
Prior exposure to cloud data warehousing — Snowflake, BigQuery, Redshift, or Fabric
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
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)