Staff Data Engineer

Role Overview

We are seeking an Analytics Engineer to design, build, and operate our analytics and automations as well as build of AI-powered automations and copilots using governed enterprise data. This role is responsible for delivering high-quality Power BI reporting, establishing and maintaining Microsoft Fabric and/or GCP BigQuery, and building business automations and applications using Python, Power Automate and Power Apps.

You will be part of the Cloud & Service Management organization helping to evolve our self-service analytics, scalable data architecture, and automations—while ensuring security, performance, and governance across the platform.

This is a hands-on role with ownership of both solution delivery and platform best practices.

Key Responsibilities

Analytics & Reporting

• Design, develop, and maintain reports and dashboards
• Build and optimize semantic models using strong dimensional modeling (star schema)
• Write and tune DAX measures with a focus on performance and usability
• Implement Power BI and Looker deployment pipelines and promote content across environments

Microsoft Fabric Platform

• Establish and maintain Microsoft Fabric architecture, including:
  • Lakehouse and/or Warehouse
  • Dataflows Gen2
  • OneLake data 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

Automation & Applications

• 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

Platform Governance & Operations

• Define Dev/Test/Prod environment strategy for reporting and automation platform
• Implement Application Life best practices (solutions, pipelines, 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

Collaboration & Leadership

• Translate business requirements into scalable technical solutions
• Contribute to platform roadmap and continuous improvement efforts

Agentic AI & ML Enablement

• Design and deliver agentic AI solutions that automate multi-step business workflows (tool use, planning, and human-in-the-loop approvals) using enterprise data and governed actions.

• Build RAG (retrieval-augmented generation) patterns over Fabric/OneLake (document ingestion, chunking, embeddings, retrieval evaluation) to power analytics copilots and self-service Q&A.

• Develop and operate ML pipelines (feature engineering, training, evaluation, batch/real-time inference) using Python and approved ML frameworks.

• Establish LLMOps/ModelOps practices: prompt/version control, offline evaluation, regression testing, monitoring (quality, drift, cost, latency), and safe rollback.

• Implement AI security and governance: data access controls, prompt/data leakage prevention, PII handling, model risk reviews, and audit logging for agent actions.

• Partner with stakeholders to identify high-value use cases and deliver measurable outcomes (time saved, defect reduction, SLA improvements).

Required Qualifications

• 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)
  • Power Apps (Canvas apps)
  • Dataverse
• Hands-on Python experience delivering ML or GenAI solutions in production (notebooks-to-service, APIs, scheduled jobs, or integrated automations).

• Working knowledge of RAG concepts (embeddings, vector search, retrieval, grounding, evaluation).

• Experience implementing monitoring and testing for data/ML/GenAI systems (data quality checks, model/prompt evaluation, logging/telemetry).

• Experience managing environments, security, and deployments
• Strong understanding of data governance and analytics best practices

Preferred Qualifications

• Experience designing enterprise-scale analytics platforms
• Familiarity with Azure services (Azure SQL, Data Factory, Synapse)
• Familiarity with GCP BigQuery and Looker
• Experience with CI/CD concepts for Power BI and Looker
• Power Platform or Microsoft analytics certifications
• Experience working in a Center of Excellence (CoE) model
• Experience with Azure OpenAI / Azure AI Foundry (or equivalent) and enterprise deployment patterns.

• Experience with orchestration frameworks (e.g., Semantic Kernel, LangChain, Autogen) and tool/function calling.

#LI-P1