Manage and enhance OneLake architecture, delta lake tables, security policies, and data governance within Fabric.
Build scalable, reusable data assets and engineering patterns that support analytics, reporting, and machine learning workloads.
Ensure data quality, lineage, cataloging, and compliance align with enterprise governance standards.
Power BI (Expert Level)
Architect and deliver enterprise Power BI solutions, including:
Robust semantic models
DAX calculations and optimizations
Row-level security (RLS) and object-level security (OLS)
Large models and composite models
Develop visually compelling, high-performance dashboards tailored to business needs.
Optimize dataset refresh strategies, gateway configurations, and incremental refresh policies.
Mentor teams in Power BI best practices, performance tuning, and data visualization standards.
Data Engineering & Integration
Build reliable ETL/ELT pipelines using Fabric Data Factory and/or existing integration platforms.
Integrate structured and unstructured data across multiple source systems.
Implement CI/CD practices for Fabric and Power BI (Git integration, deployment pipelines).
Job Requirements:
5+ yearsin data engineering, BI engineering, or analytics engineering roles.
In-depth experience with Microsoft Fabric, including lakehouse architecture, data pipelines, SQL analytics, and governance components.
Expert-level Power BI skills, including DAX, modeling, performance tuning, and advanced visualization development.
Strong SQL and Python skills; Spark experience preferred.
Solid understanding of data warehousing concepts, star schemas, and MPP engine performance optimization.
Experience with Git-based workflows, DevOps pipelines, and deployment automation.
Familiarity with Microsoft Purview and enterprise data governance frameworks.
Proven ability to design data solutions in complex, enterprise environments.
Highly Desired
Microsoft certifications such as:
DP-600(Fabric Analytics Engineer)
PL-300(Power BI Data Analyst)
Experience with large-scale data migrations into Fabric.
Exposure to cloud platforms (Azure preferred), especially ADLS, Synapse, and Databricks.
Background in data science workflows or ML integration is a plus.
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