BENGALURU · FULLTIME
Staff Data Engineer
Pearson
Bengaluru · onsite · Posted 29d ago
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Undisclosed5–10 yrsfulltimeBengaluru
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Section · 01
About this role
Job Summary
Responsibilities
Required Qualifications
Preferred Qualifications
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Job Title: Staff Data Engineer 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-including security, performance, and governance across the platform. This is a hands-on role with ownership of both solution delivery and platform best practices.
Responsibilities
- Analytics Reporting: Design, develop, and maintain reports and dashboards.
- Analytics Reporting: Build and optimize semantic models using strong dimensional modeling (star schema).
- Analytics Reporting: Write and tune DAX measures with a focus on performance and usability.
- Analytics Reporting: 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.
- Microsoft Fabric Platform: Manage Fabric capacities, workspaces, and permissions.
- Microsoft Fabric Platform: Monitor performance, cost, and reliability of Fabric workloads.
- Microsoft Fabric Platform: Develop and maintain Python-based data transformations and notebooks within Fabric.
- Microsoft Fabric Platform: Use Python for data preparation, enrichment, validation, and advanced analytics.
- Microsoft Fabric Platform: Define and enforce data modeling and medallion architecture standards.
- Automation Applications: Build and maintain automation flows for business processes, approvals, and integrations.
- Automation Applications: Work with Dataverse, connectors, and security roles.
- Automation Applications: Implement error handling, logging, and operational support patterns.
- Platform Governance Operations: Define Dev/Test/Prod environment strategy for reporting and automation platform.
- Platform Governance Operations: Implement Application Life best practices (solutions, pipelines, source control where applicable).
- Platform Governance Operations: Establish governance standards to prevent platform sprawl.
- Platform Governance Operations: Partner with security and IT teams on access control and compliance.
- Platform Governance Operations: Provide guidance and enablement to analysts and citizen developers.
- Collaboration Leadership: Translate business requirements into scalable technical solutions.
- Collaboration Leadership: 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.
- Agentic AI ML Enablement: Build RAG (retrieval-augmented generation) patterns over Fabric/OneLake (document ingestion, chunking, embeddings, retrieval evaluation) to power analytics copilots and self-service QA.
- Agentic AI ML Enablement: Develop and operate ML pipelines (feature engineering, training, evaluation, batch/real-time inference) using Python and approved ML frameworks.
- Agentic AI ML Enablement: Establish LLMOps/ModelOps practices: prompt/version control, offline evaluation, regression testing, monitoring (quality, drift, cost, latency), and safe rollback.
- Agentic AI ML Enablement: Implement AI security and governance: data access controls, prompt/data leakage prevention, PII handling, model risk reviews, and audit logging for agent actions.
- Agentic AI ML Enablement: Partner with stakeholders to identify high-value use cases and deliver measurable outcomes (time saved, defect reduction, SLA improvements).
Required Qualifications
- 5years of experience in analytics, BI, or data engineering roles.
- 3years 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.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Section · 02
Skills
AutomationCanvasAzure AiapisAzure ServicesBusiness Requirementsanalytics platformsbigqueryAzure OpenAICanvas AppsAzure SQLAnalyticsai securitycloudArchitectureAdvanced AnalyticscomplianceAi SolutionsMicrosoft AzureArtificial Intelligence
Section · Company
About Pearson
Pearson
Education & Training
10000-50000
employees
1844
182 years old
London
United Kingdom
About
Pearson delivers educational content and digital services globally, aiming to improve learners' skills and employability in a dynamic work environment.
Industries
Education & TrainingInternet
Employee ratings
144 reviews
3.6/ 5
Culture
3.4
Career growth
2.9
Work-life
3.8
Employees rate it well for
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