Business Operations & Data Specialist - Production & Quality

Business Operations & Data Specialist (Production & Quality)

Destinus · Madrid, Spain (Hybrid) · Full-time · Posted 2026-11-12

Workplace: hybrid

Department: Production & Manufacturing

Description

About the role

Behind every well-run plant is a shared understanding of how it is performing — and that understanding has to be built. As a Business Operations & Data Specialist focused on Production & Quality at Destinus, you are the bridge between the people who run our plants and the data that describes them. Plant managers, production leads, and quality engineers own the processes; our lakehouse holds the data those processes create. Your job is to connect the two, so that every production and quality figure, from the shopfloor to the leadership team, is defined by the business, built on the lakehouse, and trusted by both.

This is as much an operations role as a reporting one. You will translate what the business needs to know into what the data platform has to deliver, working with our Data Engineers on the production and quality data in the lakehouse and turning it into the reporting used across three European plants, including our Digital Shopfloor Management Solution, relied on by more than 300 people. You will also go to where the data is created and make it better there — improving how it is captured, automating what is still manual, and helping three plants work to one standard.

At Destinus, we are redefining the future of aerospace manufacturing — bringing speed, precision, and innovation to every process that powers our advanced Unmanned Aerial Vehicles (UAVs). Our operations span multiple plants and teams, and your work will directly support the reliability, efficiency, and excellence required for mission-critical production. Join us in shaping the next era of aerospace operations.

What You'll do

• Be the go-to contact between the business owners of production and quality data — plant managers, production leads, and quality engineers — and our lakehouse: turn their questions into clear data requirements, and the data back into answers they can act on.
• Own the production and quality portfolio end to end: define the KPI, improve the process behind it, build the dashboard, and stand behind the number.
• Own the production and quality domain in our lakehouse: know which tables and fields hold what, where each comes from, and who owns it at source — and keep that knowledge documented rather than in your head.
• Partner with our Data Engineers on the curated (gold) layer for production and quality: specify the tables, fields, and business rules the business needs, and validate the result against what actually happens on the shopfloor before anyone relies on it.
• Set and monitor data quality checks for your domain, and route each issue to the right owner — the person entering the data, the system configuration, or the pipeline — until it is fixed.
• Maintain and continuously improve Power BI dashboards tracking production and quality performance across all three plants, built on certified lakehouse data rather than side spreadsheets.
• Describe production and quality data in plain business language — what each field means, who owns it, and how sensitive it is — for our shared meanings layer, so that colleagues and our AI assistants can use it correctly without having to ask you first.
• Automate what is manual today: recurring reports, data collection, and the preparation behind daily and weekly performance routines.
• Support the standardisation of ways of working across the three plants, partnering with our Lean Operations Specialist so that measurement and improvement pull in the same direction.

Requirements

What You’ll Need

• Bachelor's or Master's degree in Industrial Engineering, Manufacturing, Operations, Quality Management, or a related field.
• Experience in a production or quality environment; aerospace or another regulated industry is highly preferred.
• Solid understanding of manufacturing and quality metrics — throughput, cycle time, OEE, scrap and rework, first-pass yield — and of quality processes such as non-conformance handling, customer complaints and field returns, root cause analysis, and corrective actions.
• Strong expertise in Power BI (data modeling, DAX, dashboard design, troubleshooting), complemented by advanced Excel skills.
• Comfortable querying data with SQL and working in a lakehouse or data warehouse environment; experience with Microsoft Fabric or a medallion (bronze/silver/gold) architecture is a plus. You will not build the pipelines — you need to know what to ask for and how to check what comes back.
• Able to explain data to non-technical colleagues and business needs to technical ones — and to get both sides to agree on one definition.
• Knowledge of ERP systems such as Microsoft Dynamics 365 / MSD, and familiarity with shopfloor or MES systems.
• A track record of improving or automating a process, not only reporting on it. Exposure to continuous improvement methods is a plus.
• Comfortable working across multiple sites and collaborating with production teams, quality engineers, and leadership alike.
• Fluent in English; Spanish, German or Dutch is a strong plus given our plant locations.
• Experience in a start-up or scale-up environment is preferred.

Who You Are

You are equally comfortable on a shopfloor and in a data model, and you speak both languages — the plant's and the lakehouse's. You know that the fastest way to fix a reporting problem is often to walk to the place where the data is created and ask how it gets entered — and then change it.

You are structured and persistent, because aligning three plants on one way of working takes more than a good spreadsheet; it takes patience and conversations. You enjoy the detail of a root cause but stay focused on whether performance actually improved, and when something is manual or repetitive you would rather automate it than live with it.

You turn numbers into stories, stories into priorities, and priorities into measurable change. Above all, you take ownership, challenge assumptions, and stay committed to operational excellence.

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