Sr Data Engineer (Microsoft Fabric, Power BI, and Purview)

QUALIFICATIONS

• 5+ years of experience in data engineering, analytics engineering, data platform development, or related technical roles.
• Strong SQL and Python skills, with experience building analytical data models, transformation logic, and ETL/ELT pipelines for enterprise analytics and reporting use cases.
• Experience working with cloud data platforms, preferably Microsoft Azure and Microsoft Fabric.
• Working knowledge of dimensional modeling, lakehouse patterns, and semantic modeling concepts.
• Ability to work independently while collaborating effectively with distributed teams, with strong written and verbal communication skills.
• Advanced English proficiency, written and spoken, required for daily collaboration with U.S.-based teams and client-facing engagements.
• Valid passport and up-to-date travel documentation for the United States, as occasional international travel may be required depending on client and project needs.

KEY RESPONSIBILITIES

• Design, develop, and maintain Microsoft Fabric Lakehouses, Warehouses, Data Pipelines, Dataflows Gen2, Notebooks, and OneLake-based data assets.
• Build scalable ingestion, transformation, cleansing, and validation pipelines for structured, semi-structured, and cloud-based data sources.
• Implement medallion architecture patterns across Bronze, Silver, and Gold layers to support trusted enterprise analytics.
• Develop Power BI-ready datasets and semantic models that support executive dashboards, operational reporting, and self-service analytics.
• Partner with BI developers to optimize Direct Lake, Import, and composite model approaches based on usage, scale, performance, and governance needs.
• Apply Microsoft Purview and Fabric governance practices, including metadata, lineage, and data quality controls, to improve data discoverability and compliance.
• Optimize data workloads for performance, reliability, scalability, and cost-effective capacity utilization.
• Support CI/CD, deployment pipelines, version control, documentation, monitoring, and production support for data solutions.
• Translate technical data engineering concepts into clear explanations for business users and client stakeholders.
• Collaborate with architects, analysts, data scientists, and business teams to deliver end-to-end data and analytics solutions.

PREFERRED SKILLS

• Experience supporting Power BI datasets, semantic models, and reporting environments, with strong understanding of analytics solution design.
• Strong understanding of data governance, data quality, privacy, access control, and metadata management concepts at an enterprise scale.
• Hands-on experience with Microsoft Fabric Lakehouse, Warehouse, Data Factory, Dataflows Gen2, Notebooks, OneLake, and Direct Lake.
• Experience with Microsoft Purview data catalog, lineage, classification, glossary, or governance workflows.
• Experience with Power BI performance tuning, DAX, deployment pipelines, and workspace governance.
• Experience with Azure Data Factory, Azure Data Lake, Azure SQL, Synapse, Databricks, or Delta Lake.
• Experience implementing CI/CD, Git integration, automated testing, and deployment standards for data solutions.
• Microsoft Fabric, Power BI, Azure, or Databricks certifications are a plus

WHAT WE OFFER

• Competitive salary.
• Opportunity to work on Integratz's enterprise data warehouse modernization program, applying modern Microsoft Fabric, Power BI, Purview, and Azure technology.
• A proven delivery method, Integratz's medallion architecture build pattern, not a one-off, unstructured engagement.
• Flexible, primarily remote work environment.
• Collaborative, inclusive, and multicultural consulting environment with direct exposure to enterprise-scale data transformation.
• Growth path into architecture, analytics engineering leadership, governance, or data platform strategy roles, with access to certifications and cutting-edge tools and technologies.
• Supportive team culture focused on practical delivery, client value, and continuous improvement.