The Role
Designs and develops enterprise data platforms using Microsoft Fabric and Azure. Responsibilities include architecture across OneLake, Lakehouse, pipelines, warehouses, semantic models, and Power BI; implementation of Medallion Architecture; development with PySpark, Python, SQL, and Azure Data Factory; governance, security, data quality, lineage, performance optimization, and CI/CD. The role also requires stakeholder collaboration, architecture documentation, and technical decision-making.
Summary Generated by Built In
As a Microsoft Fabric & Azure Data Platform Developer, you will:
- Design and develop enterprise data platforms using Microsoft Fabric and Azure data services.
- Define architecture across OneLake, Lakehouse, Data Warehouse, Data Pipelines, Dataflows Gen2, Notebooks, and Semantic Models.
- Design and implement Medallion Architecture for enterprise data ingestion, transformation, modelling, and consumption.
- Develop and optimize data solutions using PySpark, Python, SQL, Spark SQL, and Azure Data Factory.
- Design Power BI architecture and semantic models, including standardized KPI definitions and reporting governance.
- Define enterprise data modelling, integration patterns, APIs, and data platform modernization strategies.
- Establish and support data governance, ownership, stewardship, security, privacy, GDPR, and compliance controls.
- Implement practices for data quality, data lineage, metadata management, and master/reference data management.
- Support Azure DevOps, Git, CI/CD, release management, and deployment automation.
- Optimize data-platform performance through workload management, scalability, performance tuning, and capacity planning.
- Work closely with stakeholders to understand business and technical requirements and translate them into scalable data-platform solutions.
- Produce clear architecture documentation and contribute to technical decision-making.
What You Bring to the Table:
- 4–6 years of overall professional experience in data engineering, data platform development, data architecture, or a closely related field.
- Strong architecture experience with Microsoft Fabric and enterprise Azure data platforms.
- Hands-on expertise with Microsoft Fabric, OneLake, Lakehouse, Data Warehouse, Data Pipelines, Dataflows Gen2, Notebooks, and Semantic Models.
- Strong understanding of Medallion Architecture and enterprise data ingestion, transformation, modelling, and consumption patterns.
- Hands-on experience with PySpark, Python, SQL, Spark SQL, and Azure Data Factory.
- Experience with Power BI architecture, semantic modelling, KPI standardization, and reporting governance.
- Strong knowledge of enterprise data modelling, integration patterns, APIs, and data-platform modernization.
- Experience with data governance, data ownership, stewardship, security, privacy, GDPR, and compliance.
- Understanding of data quality, lineage, metadata management, and master/reference data concepts.
- Experience with Azure DevOps, Git, CI/CD, release management, and deployment automation.
You should possess the ability to:
- Design scalable and maintainable Microsoft Fabric and Azure data architectures.
- Translate business and technical requirements into effective data-platform architecture and implementation approaches.
- Design robust data ingestion, transformation, modelling, and consumption pipelines.
- Apply Medallion Architecture effectively across enterprise data solutions.
- Develop and optimize data processing solutions using PySpark, Python, SQL, and Spark SQL.
- Design effective Power BI semantic models and establish consistent KPI definitions.
- Implement appropriate data governance, security, privacy, GDPR, and compliance controls.
- Identify and resolve data quality, performance, scalability, and workload-management issues.
- Implement automated CI/CD and deployment processes using Azure DevOps and Git.
- Document architecture, technical decisions, integration patterns, and platform standards clearly.
- Communicate effectively with technical and business stakeholders and make sound architectural decisions.
What we bring to the table:
- An opportunity to work on modern enterprise data platforms using Microsoft Fabric and Azure.
- Exposure to advanced data architecture, analytics, data governance, and platform modernization initiatives.
- The opportunity to work with OneLake, Lakehouse, Data Warehouse, Power BI, Azure Data Factory, and modern data engineering technologies.
- A role involving architecture, hands-on data engineering, governance, performance optimization, and stakeholder collaboration.
Let’s Connect:
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Giftson Paul Davidson
Phone: +31 20 369 0609 ; Extn : 151
LinkedIn: https://www.linkedin.com/in/giftsonpauldavidson/
Skills Required
- 4-6 years of professional experience in data engineering, data platform development, data architecture, or a related field.
- Strong architecture experience with Microsoft Fabric and enterprise Azure data platforms.
- Hands-on expertise with Microsoft Fabric, OneLake, Lakehouse, Data Warehouse, Data Pipelines, Dataflows Gen2, Notebooks, and Semantic Models.
- Strong understanding of Medallion Architecture and enterprise data ingestion, transformation, modeling, and consumption patterns.
- Hands-on experience with PySpark, Python, SQL, Spark SQL, and Azure Data Factory.
- Experience with Power BI architecture, semantic modeling, KPI standardization, and reporting governance.
- Strong knowledge of enterprise data modeling, integration patterns, APIs, and data-platform modernization.
- Experience with data governance, data ownership, stewardship, security, privacy, GDPR, and compliance.
- Understanding of data quality, lineage, metadata management, and master/reference data concepts.
- Experience with Azure DevOps, Git, CI/CD, release management, and deployment automation.
- Ability to design scalable and maintainable Microsoft Fabric and Azure data architectures.
- Ability to translate business and technical requirements into effective data-platform architecture and implementation approaches.
- Ability to design robust data ingestion, transformation, modeling, and consumption pipelines.
- Ability to apply Medallion Architecture across enterprise data solutions.
- Ability to develop and optimize data processing solutions using PySpark, Python, SQL, and Spark SQL.
- Ability to design Power BI semantic models and establish consistent KPI definitions.
- Ability to implement data governance, security, privacy, GDPR, and compliance controls.
- Ability to identify and resolve data quality, performance, scalability, and workload-management issues.
- Ability to implement automated CI/CD and deployment processes using Azure DevOps and Git.
- Ability to document architecture, technical decisions, integration patterns, and platform standards clearly.
- Effective communication with technical and business stakeholders and sound architectural decision-making.
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The Company
What We Do
STAFIDE is a Netherlands-based niche technology talent consulting company operating across Europe. It helps organizations identify, recruit, and deploy technology professionals in areas including cybersecurity, cloud engineering, software development, data analytics, ERP, infrastructure, and digital transformation. Its services include recruitment, workforce engagement, secondment, onboarding support, workforce deployment, and workforce analytics that support technology hiring and expansion.
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