Staff Data Engineer

Job Title: Staff Data Engineer

About the

Role

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.

• 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.