Staff Data Engineer

Pearson VUE

. Design, develop, and maintain reports and dashboards .

Posted 9/18/2026full-timeBangalore • IndiaLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Power BI development, Microsoft Fabric architecture, and Python-based data transformations, with a strong focus on data governance and analytics best practices. Capable of translating business requirements into scalable technical solutions while implementing AI security and governance measures.

Highest-signal resume keywords

Power BI DevelopmentMicrosoft Fabric ArchitectureDAX ProficiencyPython for ML SolutionsData Governance Best Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

DAXSQLData ModelingPythonML PipelinesDimensional ModelingStar SchemaDataflows Gen2RAG ConceptsApplication Lifecycle Best Practices

Soft Skills

CollaborationGuidanceProblem-Solving

Tools & Technologies

Power BILookerPower AutomatePower AppsDataverseMicrosoft FabricAzure ServicesGCP BigQuery

Certifications & Qualifications

Microsoft Analytics Certifications

Industry Keywords

AnalyticsBusiness IntelligenceData EngineeringData GovernanceAI SecurityModelOpsGenAI Solutions

Tech Stack

Tools & technologies

AzureBigQueryCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Design, develop, and maintain reports and dashboards
Build and optimize semantic models using dimensional modeling and star schema
Write and tune DAX measures
Implement Power BI and Looker deployment pipelines
Establish and maintain Microsoft Fabric architecture, including Lakehouse/Warehouse, Dataflows Gen2, and OneLake organization
Manage Fabric capacities, workspaces, and permissions
Monitor performance, cost, and reliability of Fabric workloads
Develop and maintain Python-based data transformations and notebooks within Fabric
Use Python for data preparation, enrichment, validation, and advanced analytics
Define and enforce data modeling and medallion architecture standards
Build and maintain automation flows for business processes, approvals, and integrations
Work with Dataverse, connectors, and security roles
Implement error handling, logging, and operational support patterns
Define Dev/Test/Prod environment strategy
Implement application lifecycle best practices, including solutions, pipelines, and source control where applicable
Establish governance standards to prevent platform sprawl
Partner with security and IT teams on access control and compliance
Provide guidance and enablement to analysts and citizen developers
Translate business requirements into scalable technical solutions
Contribute to the platform roadmap and continuous improvement
Design and deliver agentic AI solutions for multi-step business workflows
Build RAG patterns over Fabric/OneLake for analytics copilots and self-service Q&A
Develop and operate ML pipelines using Python and approved ML frameworks
Establish LLMOps/ModelOps practices including evaluation, testing, monitoring, and rollback
Implement AI security and governance, including access controls, PII handling, model risk reviews, and audit logging
Identify high-value AI use cases and deliver measurable outcomes

Requirements

What you’ll need

5+ years of experience in analytics, BI, or data engineering roles
3+ years of hands-on Power BI development experience
Strong experience with Microsoft Fabric (Lakehouse, Warehouse, Dataflows)
Proficient in DAX, SQL, and data modeling
Hands-on experience with Power Automate (cloud flows, approvals, integrations)
Hands-on experience with Power Apps (Canvas apps)
Hands-on experience with Dataverse
Hands-on Python experience delivering ML or GenAI solutions in production
Working knowledge of RAG concepts (embeddings, vector search, retrieval, grounding, evaluation)
Experience implementing monitoring and testing for data/ML/GenAI systems
Experience managing environments, security, and deployments
Strong understanding of data governance and analytics best practices
Preferred: enterprise-scale analytics platforms, Azure services, GCP BigQuery, Looker, CI/CD concepts, Power Platform or Microsoft analytics certifications, Center of Excellence models, Azure OpenAI/Azure AI Foundry or equivalent, and orchestration frameworks such as Semantic Kernel, LangChain, or Autogen