{"id":1360445,"url":"https://alion.io/job/pearson-staff-data-engineer-data-coe","title":"Staff Data Engineer - Data COE","company":{"id":1785237,"name":"Pearson","domain":"pearson.jobs","url":"https://alion.io/company/pearson-jobs","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":39000,"max_usd":90000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":404},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"BigQuery","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLMOps","optional":false},{"name":"Looker","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Power Apps","optional":false},{"name":"Power Automate","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SQL","optional":false},{"name":"Tool Use","optional":false},{"name":"AutoGen","optional":true},{"name":"Azure","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"Azure SQL Database","optional":true},{"name":"CI/CD","optional":true},{"name":"LangChain","optional":true},{"name":"OpenAI","optional":true},{"name":"Semantic Kernel","optional":true}],"status":"live","first_seen_at":"2026-09-18T07:32:03Z","employer_posted_date":"2026-09-18","last_verified_at":"2026-09-27T23:46:48Z","board_verified":true,"closed_at":null,"days_open":9,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":9},"description":"Job Title: Staff Data Engineer\nAbout the Role\nWe 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.\nYou 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.\nThis is a hands-on role with ownership of both solution delivery and platform best practices.\nShift & 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.\nKey Responsibilities\nAnalytics & Reporting\nDesign, develop, and maintain reports and dashboards \nBuild and optimize semantic models using strong dimensional modeling (star schema)\nWrite and tune DAX measures with a focus on performance and usability\nImplement Power BI and Looker deployment pipelines and promote content across environments\nMicrosoft Fabric Platform\nEstablish and maintain Microsoft Fabric architecture, including: Lakehouse and/or Warehouse\nDataflows Gen2\nOneLake data organization\n\nManage Fabric capacities, workspaces, and permissions\nMonitor performance, cost, and reliability of Fabric workloads\nDevelop and maintain Python-based data transformations and notebooks within Fabric\nUse Python for data preparation, enrichment, validation, and advanced analytics\nDefine and enforce data modeling and medallion architecture standards\nAutomation & Applications\nBuild and maintain automation flows for business processes, approvals, and integrations\nWork with Dataverse, connectors, and security roles\nImplement error handling, logging, and operational support patterns\nPlatform Governance & Operations\nDefine Dev/Test/Prod environment strategy for reporting and automation platform\nImplement Application Life best practices (solutions, pipelines, source control where applicable)\nEstablish governance standards to prevent platform sprawl\nPartner with security and IT teams on access control and compliance\nProvide guidance and enablement to analysts and citizen developers\nCollaboration & Leadership\nTranslate business requirements into scalable technical solutions\nContribute to platform roadmap and continuous improvement efforts\nAgentic AI & ML Enablement\nDesign 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.\nBuild RAG (retrieval-augmented generation) patterns over Fabric/OneLake (document ingestion, chunking, embeddings, retrieval evaluation) to power analytics copilots and self-service Q&A.\nDevelop and operate ML pipelines (feature engineering, training, evaluation, batch/real-time inference) using Python and approved ML frameworks.\nEstablish LLMOps/ModelOps practices: prompt/version control, offline evaluation, regression testing, monitoring (quality, drift, cost, latency), and safe rollback.\nImplement AI security and governance: data access controls, prompt/data leakage prevention, PII handling, model risk reviews, and audit logging for agent actions.\nPartner with stakeholders to identify high-value use cases and deliver measurable outcomes (time saved, defect reduction, SLA improvements).\nRequired Qualifications\n5+ years of experience in analytics, BI, or data engineering roles\n3+ years of hands-on Power BI development experience\nStrong experience with Microsoft Fabric (Lakehouse, Warehouse, Dataflows)\nProficient in DAX, SQL, and data modeling\nHands-on experience with: Power Automate (cloud flows, approvals, integrations)\nPower Apps (Canvas apps)\nDataverse\n\nHands-on Python experience delivering ML or GenAI solutions in production (notebooks-to-service, APIs, scheduled jobs, or integrated automations).\nWorking knowledge of RAG concepts (embeddings, vector search, retrieval, grounding, evaluation).\nExperience implementing monitoring and testing for data/ML/GenAI systems (data quality checks, model/prompt evaluation, logging/telemetry).\nExperience managing environments, security, and deployments\nStrong understanding of data governance and analytics best practices\nPreferred Qualifications\nExperience designing enterprise-scale analytics platforms\nFamiliarity with Azure services (Azure SQL, Data Factory, Synapse)\nFamiliarity with GCP BigQuery and Looker\nExperience with CI/CD concepts for Power BI and Looker\nPower Platform or Microsoft analytics certifications\nExperience working in a Center of Excellence (CoE) model\nExperience with Azure OpenAI / Azure AI Foundry (or equivalent) and enterprise deployment patterns.\nExperience with orchestration frameworks (e.g., Semantic Kernel, LangChain, Autogen) and tool/function calling.","description_format":"text","description_chars":5117,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Hybrid work"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-27T23:45:59Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":9,"expected_fill_days":54,"reasons":["conf:2","win:early","comp:brand"],"computed_at":"2026-09-28T02:26:47Z"},"pay":null,"html_url":"https://alion.io/job/pearson-staff-data-engineer-data-coe","json_url":"https://alion.io/job/pearson-staff-data-engineer-data-coe.json","meta":{"generated_at":"2026-09-28T02:26:47Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1169,"day_limit":5000,"remaining_today":3831,"minute_limit":60,"resets_at":"2026-09-29T00:00:00Z"}}}