Lead Data Engineer - Data Platform & AI (w/m/d)

Worldwide | Sept. 7, 2026

Report as Closed

Company: enua Pharma GmbH

Country: Worldwide

Type: Onsite

Employment: Full-time

Description:

Are you ready to help write German cannabis history?

enua is a holistic manufacturer of medical cannabis and is one of the leading providers in this market in Germany.

We are a team of 50 motivated individuals in Cologne, united by the vision of giving people a better attitude to life through sustainable access to high-quality cannabis and of having a lasting impact on this pioneer market. With over 1,000 pharmacies as customers, we have reached a sales level of 50 million euros.

As a sustainably profitable and fast-growing company, we are looking for talented, ambitious and passionate employees. In the Data & Solutions area in particular, we are currently building a team that will shape the standards of the industry. In the IT & Data area, we laid the foundations last year - now we're building on that.

Tasks

Our data platform runs on Databricks. The basis is in place - the exciting work begins now: a data model that supports the entire company, clean integrations into ERP, CRM and market data, AI applications that are based on it, and standards that support a growing team. We are looking for you as Lead Data Engineer - Data Platform & AI (m/f/d).

You take technical ownership of the platform: architecture, data model and implementation are your decisions. You work hands-on with Python, SQL and Databricks, with end-to-end ownership from prototype to operation - and use AI-supported development (e.g. Claude Code) as a natural tool, not as an extra topic.

• Data platform responsible for: You will further develop our Databricks Lakehouse - architecture, pipelines, operations, costs - and decide what we expand and how.
• Data model Build: You design the central data model for products, customers, market and transactions - the basis for reporting, self-service and AI. You decide how much structure we need and where pragmatism wins.
• Systems Integrate: You connect ERP (Microsoft Dynamics 365 Business Central), CRM, external market data and APIs - robust, documented, monitored.
• Putting AI into use: You build LLM-based workflows, agents and internal tools that are based on the platform and take real work off of specialist departments.
• Engineering Efficiency: You automate what makes engineering slow - deployments, testing, monitoring, infrastructure as code - so that changes to the platform go into production in minutes instead of days and pipelines run reliably even without supervision.
• Technically Lead: You set the guardrails for code quality, Git workflow and documentation, review what ends up on the platform, are a sparring partner for analysts and product owners and a technical counterpart for external developers and partners.
• Work with the business: Together with our product owner, our analysts and the departments, you translate requirements into executable solutions - from a prototype in days to stable operation.

Qualification

This is what you bring with you

Several years of experience as a builder in the data/tech environment – as a senior data engineer, analytics engineer, tech lead or all-rounder. We don't care whether you already have the title Tech Lead or get it here - skill counts more than years of work.

• Databricks: You have built productively on Databricks or a comparable lakehouse stack (Spark, Delta Lake) and know how to operate a platform, not just play with it.
• Data modeling: You have designed data models that have existed in operations - dimensional modeling, master data, hierarchies - and can explain why you chose what you did.
• Python & SQL: Very good knowledge of data processing, integrations and automation.
• Experience with integrations and APIs: you connect systems that were not designed for each other. ERP experience is a plus.
• Confident handling of Git, CI/CD and clean code - and the ability to set standards in a team without creating bureaucracy.
• AI practice: You work with LLM APIs and AI-supported development tools in everyday life and ideally have already made workflows or agents productive.
• Very good knowledge of spoken and written German.
• Builder mindset: You deliver prototypes in days instead of weeks, think in terms of outcomes and bring things into operation.

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