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Open nowPosted 4 hours ago

Data Platform Manager

Destinus

Where
Zürich, ZH, Switzerland
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Your applicationOpen nowData Platform ManagerDestinus · Zürich, ZH, Switzerland
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Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
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  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 4 hours ago

The posting

About the role

As Data Platform Manager you will own Destinus's company data platform. Built on Microsoft Fabric, it brings together data from our different systems, and it serves the reporting and data agents that production, supply chain, program management, and finance work from every week.

You will own its architecture: how OneLake and our lakehouses are structured, how data lands in them from the systems we run, and how it holds up as more of the business comes to depend on it. You will lead a small team of data engineers — setting direction, reviewing their work, growing them — and you will keep building yourself. You are also the person who makes our AI ambitions possible: the foundation behind our data agents and our Company Brain is yours to design and deliver.

At Destinus we are redefining the future of aerospace manufacturing, building advanced Unmanned Aerial Vehicles (UAVs) across three European plants. The data you will work with is physical — parts, build progress, shortages, non-conformances — and the questions asked of it get harder each year as we grow. If you want a platform you can still shape rather than one already set in concrete, this is a good moment to arrive.

What You'll Do

  • Own the architecture of our Microsoft Fabric estate end to end — OneLake, our lakehouses and their bronze, silver, and gold layers, workspace and domain structure, naming conventions, and the standards that keep it coherent as it grows.
  • Lead, mentor, and grow a small team of data engineers: set priorities, review code, raise the technical bar, and develop the people.
  • Stay hands-on. You will build pipelines, notebooks, and Delta tables yourself, not only direct others who do.
  • Own the integrations that land data in OneLake from our source systems — ERP, HR, shopfloor, quality, and the business applications that come after them — choosing sensibly between Data Factory pipelines, dataflows, shortcuts, and mirroring for each source.
  • Own the gold layer and the semantic models built on it, so that Power BI reads from one governed source rather than from copies scattered around the business.
  • Work closely with our Business Operations & Data Specialists, who represent the business owners of each domain: turn their requirements into the right gold tables, agree definitions with them, and give them a platform they can query, validate, and explain to the business with confidence.
  • Own lineage across the estate: know what feeds what, be able to prove it to an auditor, and make dependencies visible rather than tribal knowledge.
  • Build the data foundation for our AI programme — the lakehouse structures, pipelines, and knowledge graph behind our Fabric data agents and our Company Brain — and deliver it to a standard that can be trusted with a real question.
  • Design and maintain the OneLake security and access model together with your team: workspace roles, access groups, and the controls that decide who sees what in the lake.
  • Keep the platform reliable, observable, and cost-aware: monitoring, alerting, recovery, and disciplined use of our Fabric capacity — including knowing what a runaway notebook costs us.

Requirements

What You’ll Need

Requirements

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
  • 5-8 years of data engineering experience, including real ownership of a lakehouse architecture rather than only delivering against someone else's.
  • Hands-on Microsoft Fabric experience is strongly preferred — OneLake, lakehouses, Delta tables, the SQL analytics endpoint, Data Factory pipelines, Spark notebooks, and semantic models in Direct Lake mode. If your depth is in Azure Synapse, Databricks, or Data Lake Storage Gen2 and you have since moved onto Fabric in earnest, we will take that seriously.
  • Strong command of the medallion pattern and of Delta Lake in practice: partitioning, schema evolution, table maintenance, and why a gold table behaves the way it does.
  • Genuinely hands-on. Strong SQL, solid PySpark, and comfort building and orchestrating pipelines yourself. This is not a role that stops at diagrams.
  • Practical understanding of Fabric capacity: how workloads consume it, how to spot what is burning it, and how to keep the platform inside its envelope.
  • Experience leading engineers — formally, or as a technical lead who set direction and mentored others. A first step into people management is welcome if the technical leadership is already there.
  • Proven integration experience with ERP systems such as Microsoft Dynamics 365 / MSD, as well as APIs, flat-file landings, and change data capture from operational databases.
  • Solid data modelling skills, including dimensional modelling and an understanding of how a semantic layer serves Power BI.
  • Working knowledge of lineage, data governance, and access control in a cloud platform; exposure to Microsoft Purview is a plus.
  • Interest or experience in the data foundations behind AI assistants — retrieval, knowledge graphs, and preparing data so that an agent can answer with it.
  • Aerospace or another regulated industry is an advantage; so is experience in a start-up or scale-up.
  • Fluent in English; additional European languages are a plus.

Who You Are

You are an architect who never stops building. You have strong opinions about how a platform should be structured, and you earn the right to them by being in the code. You would rather make a design decision explicit and documented than let it live in one person's head.

You care more about reliability than novelty. You know that the measure of a data platform is whether people trust the numbers that come out of it on a Monday morning, not how modern the stack looks on a slide. When something breaks, you want to know why it was possible, not just how to patch it.

You enjoy growing engineers, and you understand that leading a small team means doing the work alongside them. Above all, you want to build something durable — a foundation that holds while the company scales on top of it.

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