About this role.
This senior contract role will assess and help design a modern Azure-based data platform for finance, operations/supply chain, and quality/manufacturing reporting. The initial six-week discovery engagement combines data-estate assessment, lakehouse architecture design, technology evaluation, and hands-on proof-of-concept work. The engineer will work with a Solution Architect, Delivery Manager, Azure DevOps Engineer, and client stakeholders to recommend a pragmatic implementation roadmap. Core requirements include Azure Data Factory, Microsoft Fabric, SQL, Python or PySpark, data integration, Power BI, and CI/CD experience. Subject to client approval, the engagement may progress into a longer-term full-time platform implementation role.
Role DNA
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4/5Autonomy Level
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Core skills
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Sample interview questions
I would begin with stakeholder interviews and a structured inventory of source systems, owners, data volumes, refresh needs, integration methods, and reporting dependencies. I would document current-state flows, profile critical data entities and quality issues, identify security and operational constraints, and prioritize use cases by business value and delivery risk. The outcome would be a target architecture, a sequenced roadmap, and a narrowly scoped PoC with measurable success criteria.
I would assess each option against required ingestion patterns, transformation complexity, data volumes, team skills, Power BI integration, governance, CI/CD maturity, performance, and total operating cost. Fabric is compelling where an integrated lakehouse and Power BI-centric operating model fit the needs, while Databricks may be preferable for more advanced engineering or Spark-intensive workloads. Azure Data Factory can remain valuable for orchestration and broad connector support, potentially in a hybrid design.
The bronze layer would retain immutable, source-aligned extracts with load metadata and auditability. The silver layer would apply standardization, deduplication, quality rules, conformed keys, and incremental transformation logic across systems. The gold layer would provide business-ready dimensional models, curated marts, and semantic models optimized for Power BI, with lineage, testing, and access controls implemented throughout.
I would use metadata-driven ingestion where appropriate, parameterized pipelines, version-controlled code, automated deployment through Azure DevOps, and separate environments for development, testing, and production. Reliability controls would include data-quality tests, schema-drift handling, idempotent loads, retry and alerting policies, observability dashboards, and documented runbooks. I would also establish clear ownership and service-level expectations for critical datasets.
I would translate the recommendation into business outcomes such as trusted reporting, faster data availability, reduced manual effort, and controlled operating costs. For technical audiences, I would provide diagrams, assumptions, trade-offs, integration patterns, security considerations, and implementation estimates. I would explicitly identify decisions required, risks, and the evidence from the discovery findings so stakeholders can make an informed, practical choice.
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 Azure Data Engineer with architecture exposure, interested in assessing, designing, and potentially building a modern data platform to support Finance, Operations/Supply Chain, and Quality/Manufacturing functions.
**Expected Involvement: 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.
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 current landscape spans roughly nine source systems across Business Central, legacy NAV, QuickBooks and other integrations, with reporting currently relying on a mix of direct ERP/SQL connections and Power BI.
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 and data flows
Identify key architectural, data-quality and integration gaps
Design the target lakehouse / medallion architecture
Evaluate Microsoft Fabric, Azure Data Factory and Databricks and recommend the most suitable approach
Define the first implementation / PoC scope and 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.
About the Role
This is a hands-on Senior Data Engineer role with strong architecture exposure.
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.
During the initial six weeks, the role will combine technical discovery, architecture design and hands-on prototyping. You will help assess the existing environment, define the target approach, make technology recommendations, and contribute to building and validating an initial PoC that demonstrates the proposed solution.
If the project proceeds into implementation, the role is expected to become considerably more hands-on and may transition into a long-term, full-time engagement.
Responsibilities
Assess the current data estate, including source systems, integrations, ETL/data flows, Power BI dependencies and existing Fabric components
Understand and document existing data flows and technical dependencies, helping preserve critical knowledge of the current environment
Identify data-quality, integration, scalability and maintainability issues
Contribute to the design of the target bronze / silver / gold lakehouse architecture
Define scalable ingestion and transformation patterns for multiple ERP and other enterprise data sources
Evaluate Microsoft Fabric, Azure Data Factory and Databricks and contribute to the platform recommendation
Assess technical trade-offs including platform fit, maintainability, performance and operating cost
Define the first end-to-end PoC together with its scope and technical success criteria
Contribute to implementation estimates, sequencing and the wider technical roadmap
Collaborate closely with the Solution Architect and client stakeholders throughout Discovery
Potentially transition into hands-on implementation of the platform following client approval
Essential knowledge, skills & experience
6+ years of experience in data engineering, BI or enterprise data platforms
Strong hands-on experience with the Microsoft Azure data ecosystem
Strong experience with Azure Data Factory and modern data lake / lakehouse architectures
Practical commercial experience with Microsoft Fabric, including Lakehouse and/or Warehouse components
Advanced SQL / T-SQL
Experience with Python and/or PySpark
Strong understanding of ETL/ELT, data integration and medallion architecture patterns
Experience designing solutions that integrate multiple enterprise source systems
Good understanding of Power BI, dimensional modelling and semantic-layer concepts
Experience with Git, Azure DevOps and CI/CD practices in data-platform environments
Experience contributing to technical discovery, architecture design, technology selection, estimation or implementation planning
Ability to assess existing systems, identify architectural issues and recommend pragmatic solutions rather than simply implement predefined requirements
Strong English and confidence communicating with both technical and business stakeholders
Nice-to-have
Experience evaluating Fabric vs. Databricks and/or other Azure data-platform approaches
Fabric capacity monitoring, SKU sizing or cost-optimisation experience
Experience building or evaluating cloud/data-platform consumption and operating-cost models
Metadata-driven ETL framework experience
Multi-ERP integration experience, particularly with Business Central, NAV, QuickBooks or SAP
Experience with Purview, Databricks or Synapse
Strong Power BI experience including DAX or Tabular modelling
Experience within pharmaceutical, manufacturing or other regulated environments
Knowledge of GxP environments — domain knowledge can be learned
Interview Steps
GT interview with Recruiter
Technical interview
Final interview
Offer
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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