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
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
Who we are:
At Pearson, our purpose is simple: to help people realize the life they imagine through learning. We believe that every learning opportunity is a chance for a personal breakthrough. We are the world's lifelong learning company. For us, learning isn't just what we do. It's who we are. To learn more: We are Pearson.
Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing [email protected].
Job: Engineering
Job Family: TECHNOLOGY
Organization: OCTO
Schedule: FULL_TIME
Workplace Type: Hybrid
Req ID: 23686
