Data Engineer

Job Title: Power BI Lead

Location:

Domain:

About the Role

Power BI Lead

single source of truth

Key Responsibilities

1. Platform Architecture & Governance

• Architect and implement

  Power BI workspace and app architecture

  for secure, scalable, and organized content management across Dev, Test, and Production.
• Define governance frameworks for

  dataset certification, role-based access, and content lifecycle management

  .
• Establish

  semantic models

  and shared datasets to enable reusability and enterprise consistency.
• Integrate Power BI with

  enterprise data gateways (on-prem, VNet, and cloud)

  ensuring encrypted, audit-ready connectivity.

2. Deployment Pipelines & CI/CD

• Design and manage

  Power BI Deployment Pipelines

  for automated content promotion (Dev → Test → Prod).
• Configure

  parameterized data connections

  for seamless environment switching.
• Implement

  validation workflows

  and

  approval gates

  for controlled releases and data accuracy assurance.

3. Data Modeling & Performance Engineering

• Lead model design for

  Import, DirectQuery, Composite, and Live Connection

  modes.
• Optimize performance using

  query folding, partitioning, and computation pushdown

  to source systems.
• Establish DAX modeling best practices, calculation groups, and measures for high-performance analytics.

4. Security & Compliance

• Implement

  Row-Level Security (RLS)

  and

  Object-Level Security (OLS)

  across datasets.
• Collaborate with IT Security to enforce encryption, tenant-level governance, and usage monitoring.
• Oversee data lineage, metadata tagging, and compliance with regulatory frameworks (GDPR, SOX, etc.).

5. Automation & Integration

• Integrate Power BI with

  Power Apps, Power Automate, and Azure Data Factory

  for analytics-to-action workflows.
• Implement

  dataflows and shared ETL logic

  to enable reusable and self-service data preparation.
• Automate report scheduling, distribution, and monitoring for production-grade reliability.

6. AI & Copilot Enablement

• Leverage

  Power BI Copilot

  and natural-language Q&A capabilities for business-user-driven insights.
• Drive AI-assisted visualization, auto-report generation, and semantic search adoption.

7. Stakeholder Leadership

• Partner with business units, data engineers, and governance leads to ensure alignment between data, reporting, and analytics goals.
• Mentor Power BI developers, analysts, and business teams on advanced DAX, modeling, and performance tuning.
• Define KPIs for adoption, data trust, and report performance.

Required Skills & Experience

• 8+ years of experience in BI/Analytics with at least 4+ years in

  Power BI and enterprise deployment

  .
• Strong expertise in:
• Power BI Service, Desktop, and Premium capacities
• Dataflows, Gateways (Enterprise/VNet/Personal), and workspace governance
• Semantic modeling (Import, DirectQuery, Composite, Live)
• DAX, performance tuning, and query optimization (Query Folding, Storage Mode design)
• CI/CD via Deployment Pipelines and parameterized environments
• RLS, OLS, tenant-level governance, and security configuration
• Integration with Azure ecosystem and Power Platform (Power Apps, Automate)
• Proficiency in

  data visualization design principles, accessibility, and storytelling

  .
• Working knowledge of

  AI features (Copilot, Q&A, auto-insights)

  and

  report distribution automation

  .
• Familiarity with

  Snowflake, Synapse, Databricks, or other enterprise data warehouses

  is a plus.

Preferred Qualifications

• Microsoft Certified:

  Power BI Data Analyst Associate

• Experience leading BI modernization or SSOT (Single Source of Truth) initiatives
• Background in data governance, MDM, or metadata management tools (e.g., Atlan, Collibra, CDGC)

What You’ll Deliver

• A scalable, secure, and automated

  Power BI ecosystem

  aligned with enterprise data strategy
• Standardized

  semantic models

  and certified datasets powering cross-domain reporting
• Optimized performance through

  query folding and DAX tuning

• Seamless

  Dev/Test/Prod CI/CD pipeline

  for governed BI releases
• Adoption of

  AI-driven analytics and self-service enablement