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Salary
≈ $39k – $90k per year (Estimated)
Location
Hybrid (Bengaluru, India)
Seniority
Staff · 5+ years exp

Confirmed on the employer's own hiring board on Sep 27, 2026. First seen by Alion on Sep 18, 2026.

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Pearson is a fast-growing, exciting place to work with tremendous opportunities for personal growth and professional advancement. Take a look through All of our Jobs/Careers. Pearson Jobs.

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.

Shift & Work Location: The candidate will work US shift timings and remotely for the initial 6 months. From month 7 onwards, the role transitions to UK/US business hours with a hybrid working model from the office.

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.
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