[All remote jobs](https://jobicy.com/jobs.md)Open role[![GT logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/6f6103a3-221.jpeg)](https://jobicy.com/company/gt.md)Remote opportunity at[GT](https://jobicy.com/company/gt.md) # Senior Azure Data Engineer | KD Pharma Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/gt.md)Share27 Aug 2026Published35Listing views1Application actions26 Sep 2026Apply before Opportunity details ## About this role. AI SummaryThis 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 A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThe role requires senior-level technical breadth across Azure data engineering, architecture trade-offs, enterprise integrations, and platform cost and maintainability decisions. It also requires independently navigating an undocumented legacy landscape while communicating recommendations to technical and business stakeholders. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$155,000US market range$135k–$180k0$198k AI insightNo actual salary, pay range, rate, or compensation amount is disclosed. The figures are estimated US-market annual base-salary benchmarks in USD for a senior Azure Data Engineer with data-platform architecture and Microsoft Fabric experience; contract rates may differ materially from salaried compensation. ## Core skills Skills and capabilities most closely associated with this opportunity. [Azure Data Factory](https://jobicy.com/jobs?search_keywords=Azure%20Data%20Factory.md)[Microsoft Fabric](https://jobicy.com/jobs?search_keywords=Microsoft%20Fabric.md)[Azure Lakehouse](https://jobicy.com/jobs?search_keywords=Azure%20Lakehouse.md)[Data Architecture](https://jobicy.com/jobs?search_keywords=Data%20Architecture.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[PySpark](https://jobicy.com/jobs?search_keywords=PySpark.md)[ETL/ELT](https://jobicy.com/jobs?search_keywords=ETLELT.md)[Power BI](https://jobicy.com/jobs?search_keywords=Power%20BI.md)[Azure DevOps CI/CD](https://jobicy.com/jobs?search_keywords=Azure%20DevOps%20CICD.md) Sample interview questionsHow would you approach the six-week discovery phase for a data estate spanning Business Central, NAV, QuickBooks, and other integrations?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. How would you evaluate Microsoft Fabric, Azure Data Factory, and Databricks for this platform? 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. Describe how you would design a bronze, silver, and gold lakehouse architecture for ERP and operational data. 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. What practices would you use to make data pipelines maintainable and reliable? 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. How would you communicate an architectural recommendation to both technical teams and business stakeholders? 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 Show more [Apply now >](https://jobicy.com/jobs/151908-senior-azure-data-engineer-kd-pharma.md) > Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. 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