Senior Data / Power BI Engineer | KD Pharma at GT (Europe-Based Candidates Only )Senior Data / Power BI Engineer | KD Pharma

GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands. On behalf of KD Pharma, GT is looking for a Senior Data / Power BI Engineer with strong Azure data engineering experience, deep Power BI expertise, and the ability to independently reverse-engineer and modernize a complex, largely undocumented data and reporting environment.

**Expected Involvement: The engagement is expected to begin with a 6-week discovery phase of approximately 20-30 hours per week. Following successful completion of the discovery phase and client approval, there is potential to transition into a long-term, full-time implementation role.

Founded in 1988, KD Pharma is a technology-driven CDMO (Contract Development & Manufacturing Organization) specializing in pharmaceutical and nutraceutical production, including ultra-pure Omega-3 concentrates. The company operates internationally, with locations across Germany, Norway, the UK, the USA, Canada and Peru, and provides end-to-end solutions from development and custom synthesis through to finished dosage forms.

KD Pharma is looking to modernize its current data and reporting environment and establish a scalable, maintainable Microsoft-based data platform supporting multiple business systems and reporting needs. The current landscape spans multiple source systems across Dynamics NAV, Business Central SaaS, QuickBooks, Azure SQL, Excel/SharePoint and other integrations. Group-wide reporting currently relies heavily on Power BI, with significant transformation and business logic implemented directly within Power BI models and dataflows. The engagement will initially start with a 6-week Discovery Phase, focused on understanding the existing data estate and defining the target architecture, platform approach and implementation roadmap. During Discovery, the team will:

• Assess the existing data landscape, integrations, data flows and Power BI dependencies
• Reverse-engineer and document critical parts of the existing reporting and data environment
• Identify key architectural, data-quality and integration gaps
• Design the target bronze / silver / gold architecture and dimensional data models
• Evaluate Microsoft Fabric, Azure Data Factory and Databricks and recommend the most suitable approach
• Define how transformation logic currently embedded in Power BI can be progressively moved into a proper upstream data-processing layer
• Stabilize critical parts of the existing reporting environment where required during the transition
• Define the first implementation / PoC scope, with the group sales reporting flow expected to be one of the key end-to-end use cases
• Define the roadmap for the subsequent build phase

If Discovery is successful and the client approves the implementation, the project is expected to continue into a longer-term build phase, starting with the agreed PoC and expanding into implementation of the wider data platform.

This is a highly hands-on Senior Data / Power BI Engineer role combining data engineering, Power BI platform expertise and technical discovery. You will work closely with the Solution Architect, Delivery Manager, Azure DevOps Engineer and client stakeholders to understand the current environment, challenge existing patterns and help define a practical target architecture. A key objective is to move transformation and data-preparation logic out of complex Power BI models and into scalable upstream pipelines and properly modelled fact/dimension tables, while ensuring that existing business-critical reporting continues to operate during the transition.

• Assess and reverse-engineer the existing data and Power BI environment, including key data flows, dependencies and undocumented logic
• Stabilize critical reporting and data processes during the transition, including refresh, performance and data-flow issues
• Design and build scalable ETL/ELT pipelines that move transformation logic out of Power BI into the appropriate upstream data layer
• Design reusable dimensional models and bronze / silver / gold data structures for reporting and analytics
• Integrate and standardize data across multiple ERP and business systems, including handling inconsistent schemas and master data
• Contribute to the selection and design of the target Azure data platform, evaluating ADF, Databricks and Microsoft Fabric where appropriate
• Build and validate the initial end-to-end PoC and contribute to the implementation roadmap
• Work closely with the Solution Architect and client stakeholders while operating independently on investigation, technical decisions and delivery

Essential knowledge, skills & experience

• 6+ years of experience in data engineering, BI or enterprise data platforms
• Strong hands-on experience with Azure data services, especially Azure Data Factory, Azure SQL, Azure Synapse Analytics and Azure Data Lake Storage Gen2 (ADLS)
• Strong T-SQL / Microsoft SQL Server experience, including legacy environments
• Strong Power BI expertise beyond dashboard creation, including semantic models, DAX, Power Query/M and dataflows
• Strong understanding of ETL/ELT, dimensional modelling and bronze / silver / gold architecture patterns
• Experience modernizing or reverse-engineering complex, poorly documented data environments
• Experience integrating data from multiple enterprise systems and moving transformation logic into scalable upstream pipelines
• Strong English and ability to work independently with both technical and business stakeholders

Nice-to-have

• Commercial Microsoft Fabric experience
• Databricks, Python and/or PySpark experience
• Experience with Dynamics NAV, Business Central, QuickBooks or similar ERP/accounting systems
• Experience with Power BI platform administration, governance, deployment or CI/CD
• Experience in manufacturing, pharmaceutical or other regulated environments

Interview Steps

• GT interview with Recruiter
• Technical interview
• Final interview
• Offer