Job summary:The Senior Associate – Data Analytics, Business Intelligence & Microsoft Fabric will be responsible for designing, developing, and supporting scalable analytics and business intelligence solutions using Microsoft Power BI and Microsoft Fabric.The role combines business intelligence development, big data processing, data modeling, visualization, advanced analytics, and insight generation.The candidate will be expected to manage analytics deliverables across the full lifecycle, including requirements analysis, data acquisition, transformation, modeling, visualization, validation, deployment, monitoring, and continuous enhancement. The role will also contribute to data governance, documentation, platform optimization, self-service analytics, and the development of reusable enterprise data products.Location: Hyderabad/Kolkata, India.Key responsibilities:Business Intelligence and PowerBI developmentDesign, develop, deploy, and maintain interactive Power BI dashboards, reports, scorecards, and analytical applicationsTranslate business requirements and analytical questions into scalable and intuitive business intelligence solutionsDevelop enterprise-grade semantic models that support consistent KPI definitions, reusable calculations, and self-service reportingCreate advanced DAX measures, calculated tables, calculated columns, time-intelligence calculations, and energetic business metricsUse Power Query and M to ingest, cleanse, transform, and prepare data from multiple sourcesApply dimensional modeling principles, including star and snowflake schemas, to develop efficient and scalable reporting modelsDesign executive, operational, and analytical dashboards that clearly communicate performance, trends, risks, and opportunitiesImplement drill-through, bookmarks, tooltips, row-level security, object-level security, and other relevant Power BI capabilitiesOptimize data models, DAX calculations, visuals, report interactions, and refresh processes to improve performance and usability2 Microsoft Fabric developmentDesign, develop, and maintain analytics solutions using the Microsoft Fabric ecosystemBuild and support solutions using: Microsoft Fabric LakehouseFabric Data WarehouseData Factory PipelinesDataflows Gen2Fabric NotebooksOneLakeSemantic ModelsPower BIDevelop scalable ETL and ELT processes to acquire, transform, integrate, and publish data for analytics consumptionCreate pipelines and notebooks for batch-based data ingestion and transformationUse SQL, Python, and PySpark to process structured and semi-structured datasetsDevelop curated data layers that support reporting, analytics, and downstream business use casesContribute to the implementation of medallion or similar layered data architecture patterns, where applicableSupport development, testing, deployment, and production monitoring across analytics environmentsImplement parameterization, configuration management, logging, reconciliation, exception handling, and restart capabilities in data workflows3 Insight generation and Advanced AnalyticsAnalyze business, marketing, customer, digital, campaign, operational, and performance data to identify trends, patterns, risks, anomalies, and growth opportunitiesMove beyond reporting what happened by investigating why it happened, what it means, and what action should be consideredGenerate actionable insights that support strategic, tactical, and operational decision-makingConduct exploratory data analysis,



root-cause analysis, variance analysis, trend analysis, segmentation, cohort analysis, and performance-driver analysisInterpret relationships across multiple datasets and connect analytical findings to business outcomesDevelop hypotheses, define analytical approaches, validate findings, and present evidence-based conclusionsIdentify underperformance, outliers, emerging trends, measurement gaps, and optimization opportunitiesDevelop analytical views that differentiate signals from routine fluctuationsSupport forecasting, propensity analysis, classification, clustering, predictive analytics, and other advanced analytical use cases, where appropriate4 Data storytelling and Executive communicationConvert complex analysis into clear, concise, and compelling business narrativesCreate executive-ready presentations, insight summaries, performance commentary, and business review materialsCommunicate not only data points but also the business context, contributing factors, implications, and recommended actionsTailor analytical communication to different audiences, including business users, technical teams, functional leaders, and senior leadershipPresent analytical findings with a logical storyline supported by appropriate visualizationsClearly articulate data limitations, assumptions, dependencies, risks, and confidence levelsDevelop commentary that explains the most material changes in KPIs and performance driversFacilitate business reviews and analytical discussions, helping stakeholders interpret and act on the findings5 Business partnership and requirements managementPartner with business stakeholders to understand strategic priorities, operational processes, reporting requirements, and analytical questionsLead or support requirements-gathering discussions, discovery workshops, design reviews, demonstrations, and user-acceptance sessionsTranslate business needs into documented functional requirements, analytical requirements, data requirements, KPIs, and acceptance criteriaChallenge ambiguous requests and help stakeholders define the decisions or actions that the analytics solution should supportConduct stakeholder demonstrations and incorporate structured feedbackSupport user acceptance testing by developing test scenarios, expected outcomes, and issue-resolution tracking6 Data Quality, Governance, Security, and ControlsEmbed data quality controls within ingestion, transformation, modeling, and reporting workflowsValidate that reporting outputs reconcile with approved source systems and documented business rulesDefine and monitor relevant data-quality measures and thresholdsInvestigate data-quality exceptions and coordinate remediation with source-system owners and data teamsMaintain business definitions, KPI logic, data dictionaries, source-to-target mappings, calculation specifications, and technical documentationSupport data lineage and metadata-management practices across analytics assetsApply appropriate role-based access, row-level security, workspace permissions,



and data-classification requirementsEnsure that analytics products comply with applicable organizational security, privacy, retention, and governance standardsPromote consistent business definitions and a single source of truth across dashboards and reportsPrevent the uncontrolled duplication of measures, datasets, transformation logic, and reporting productsMaintain auditability of transformations, calculations, changes, releases, and validation resultsParticipate in peer reviews, design reviews, release controls, and production-readiness assessmentsIdentify governance gaps and recommend improvements to increase trust, transparency, and maintainability7 Testing, Deployment, and Production SupportDevelop and execute unit testing, integration testing, data validation, regression testing, and performance testingValidate data across source, transformed, curated, semantic, and visualization layersPrepare test evidence and resolve defects before production releaseSupport controlled deployments across development, testing, and production environmentsUse version control and deployment practices to maintain consistency and traceabilityMonitor scheduled refreshes, pipeline execution, semantic model processing, and dashboard availabilityTroubleshoot production issues and perform root-cause analysis8 Continuous improvement and Team contributionIdentify opportunities to automate manual reporting, repetitive transformations, reconciliations, and quality checksRecommend improvements to analytics architecture, development standards, delivery processes, and governance controlsCreate reusable templates, code components, calculation libraries, documentation standards, and development acceleratorsConduct peer reviews for Power BI reports, semantic models, SQL scripts, notebooks, and pipelinesMentor associates and junior team members in analytics, Power BI, Microsoft Fabric, data modeling, and insight-generation practicesContribute to team onboarding, knowledge-sharing sessions, technical documentation, and capability developmentStay informed about relevant developments across Microsoft Fabric, Power BI, cloud analytics, artificial intelligence, and business intelligenceEducation:Bachelor’s degree in Data Analytics, Data Science, Computer Science, Information Technology, Engineering, Statistics, Mathematics, Economics, or another relevant quantitative disciplineAn equivalent combination of relevant education and professional experience may also be consideredProfessional experience:4–7 years of experience in business intelligence, data analytics, data engineering, reporting, or a related disciplineAt least 3 years of hands-on experience developing Power BI reports, dashboards, semantic models, and analytical solutionsHands-on experience working with Microsoft Fabric or a comparable modern cloud analytics platformExperience working with large, complex, and multi-source datasetsExperience working in an Agile, iterative, or structured analytics delivery environmentExperience in marketing analytics, digital analytics, customer analytics, campaign analytics, commercial analytics, or revenue analyticsExperience with Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, or related Azure servicesFamiliarity with CI/CD, deployment pipelines, automated testing, and DevOps practices for analytics. Knowledge of Tableau, Qlik, Alteryx, or other business intelligence and data-preparation

📌 Senior Associate - Data Analytics (Hyderabad)
🏢 Grant Thornton INDUS
📍 Hyderabad