About the Role
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.
About the Client
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.
About the Project
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 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.
Responsibilities
- 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.
Engagement Structure
The engagement is expected to begin with a 6-week discovery phase of approximately 30 hours per week (180 hours total). Following successful completion of the discovery phase and client approval, there is potential to transition into a long-term, full-time implementation role.
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.