Top Data Analyst Jobs in Chennai

Analyzes and integrates large data volumes from multiple sources, identifies trends and patterns, applies statistical techniques, and develops actionable recommendations. Presents findings clearly to support data-driven decisions, collaborates with business partners, monitors recommendation outcomes, and ensures data handling complies with company standards.

Analyze internal fraud risk across business lines by creating recurring management reports, identifying emerging trends and root causes, leading advanced analytical projects, mining complex data sources, assessing control effectiveness, and recommending risk mitigation enhancements. The role collaborates with stakeholders to strengthen fraud risk policies, procedures, monitoring, and governance.

Lead fraud and operational risk analytics, recurring management reporting, data validation, reconciliation, trend analysis, root-cause investigation, control effectiveness reviews, and advanced analytical projects. The role provides actionable risk insights, supports cross-functional stakeholders, and helps migrate analytical data assets, reporting solutions, and monitoring processes to cloud platforms including Azure, Databricks, and cloud data warehouses.

Analyzes and interprets data from databases and Excel files, develops operational and management reports, validates and reconciles data, identifies discrepancies, supports root-cause analysis, and improves reporting processes through automation. Requires advanced Excel expertise and basic to intermediate MySQL knowledge, with familiarity with BI tools and healthcare or revenue cycle data preferred.

Writes and optimizes SQL queries, manages Excel-based reporting and automation, supports ETL workflows, collaborates with stakeholders on data requirements, provides actionable insights, and ensures data quality, consistency, and integrity across systems.

Designs and maintains Power BI dashboards, semantic models, and analytical solutions for multiple business functions. Develops Power Apps and Power Automate solutions using SharePoint, Dataverse, SQL, data lakes, and Databricks. Analyzes SAP data, translates business requirements into scalable solutions, supports testing and deployment, and ensures data quality, governance, security, documentation, and compliance.

Analyzes large US mortgage datasets, prepares dashboards and MIS reports, validates and reconciles data, and ensures accurate delivery within service-level deadlines. The role requires knowledge of Conventional, FHA, VA, and USDA loans, mortgage processes and regulations, and advanced Microsoft Excel. The analyst coordinates with Transaction Managers, handles ad hoc reporting requests, identifies discrepancies, and improves reporting efficiency while maintaining data quality across multiple systems.

Collects, cleans, validates, and analyzes data from multiple sources; writes SQL queries; builds reports and dashboards; identifies trends and data quality issues; documents analytical processes; collaborates with business and technical stakeholders; and presents actionable insights while following data governance and security standards.

Analyzes banking and capital-markets data, writes SQL queries, builds dashboards, and translates technical findings into leadership reports. Develops functional requirements from business needs, applies statistical and analytical methods, interprets results, assesses risk, and makes recommendations. Uses Tableau, Power BI, Excel, Python, and R. Provides guidance to team members and supports compliance, controls, and timely delivery of analytics services.

Develops dashboards, KPI scorecards, and reporting solutions; analyzes business data to identify trends, risks, and improvement opportunities; writes SQL; automates recurring reporting and data preparation; maintains certified data models, definitions, documentation, and governance standards; and delivers actionable insights to stakeholders across the business.

Analyze homeowners insurance data to support pricing, underwriting, retention, product, and competitive intelligence decisions. Write SQL across BigQuery and SQL Server, build Power BI dashboards, identify portfolio trends and anomalies, measure product changes, and ensure data quality through QA and reconciliations. The role partners with product managers and business leaders, requiring autonomous problem-solving, clear communication, and cross-functional analysis.

Leads enterprise data engineering, warehousing, integration, analytics, reporting, and regulatory data initiatives for banking and financial services. Designs scalable pipelines and data platforms, develops Oracle SQL and PL/SQL solutions, builds BI dashboards, manages data quality and governance, supports lending, risk, securities, tax, payments, treasury, and customer data domains, and provides L2/L3 production support. Partners with senior stakeholders and leads global teams to improve reporting accuracy, compliance, reconciliation, and operational performance.

Leads enterprise data engineering, analytics, reporting, regulatory data, and platform initiatives for banking and financial services. Designs data warehouses, lakes, pipelines, integrations, reporting marts, dashboards, and Oracle solutions. Ensures data quality, governance, reconciliation, lineage, and regulatory compliance across lending, risk, securities, tax, payments, treasury, and customer data. Provides L2/L3 production support, resolves incidents, drives performance improvements, and partners with senior stakeholders and global teams.

Owns payroll implementation data by extracting, cleaning, mapping, loading, and reconciling employee, compensation, tax, benefits, and retirement data. Performs validation and audit checks, verifies deductions and contribution limits, documents variances, maintains loading records, and updates project and ticketing systems. Works with US implementation specialists to ensure accurate client onboarding and first payroll processing.

Conduct media, social listening, influencer, and predictive analytics research for agency clients. Manage recurring and ad hoc KPI reporting, trend analysis, crisis monitoring, and optimization recommendations. Translate data into strategic insights and compelling stories, advise account teams and leadership, and mentor junior analysts. Support consumer, technology, healthcare, and food and beverage accounts while using specialized social listening tools and Boolean queries.

Bridges data science, engineering, and business teams by identifying AI use cases, translating business goals into analytics solutions, validating AI/ML outputs, communicating insights, and tracking KPIs. Uses SQL, dashboards, and analytics platforms to support telecom business applications and drive adoption of data science solutions.

Analyze and integrate Salesforce data across CPQ and billing projects. Support enterprise-grade CPQ design and implementation across regions and billing systems, perform data gap analysis, manipulation, standardization, and large-dataset comparisons. Apply knowledge of subscriptions, order orchestration, activation, revenue recognition, invoicing, taxation, payments, general ledger processes, and the Salesforce CPQ data model.

Design, clean, analyze, and visualize data using SQL and Python; build Tableau dashboards; apply statistics and basic ML/DS concepts; follow software/data-engineering practices (version control, unit testing, high-performance code); work with structured and unstructured data and cloud environments.

The Data Analyst develops and maintains Power BI dashboards, datasets, data models, SQL and DAX solutions, and data pipelines. The role supports AWS cloud analytics integration, data quality, troubleshooting, governance, documentation, and workspace administration. It coordinates data engineers, translates business requirements into technical deliverables, collaborates with stakeholders, and communicates findings to nontechnical audiences while supporting agile delivery and data privacy compliance.

Lead and deliver advanced analytics and machine learning solutions across Sales, Vendor Management, Cloud, eCommerce, Finance, and Supply Chain. Scope projects, build and deploy predictive models, produce executive-ready insights, and partner cross-functionally to drive revenue, operational efficiency, and strategic decisions.

Analyze operational data and processes, identify bottlenecks, design scalable solutions, automate workflows and reporting with Python and SQL, build dashboards and monitoring, perform root-cause analysis, document logic and collaborate with product, engineering, and ops teams to improve automation and data quality.

Lead complex data discovery, enrichment, curation, and AI-driven research initiatives. Develop scalable workflows for entity resolution, information extraction, taxonomies, ontologies, and knowledge graphs. Collaborate with product teams, customers, and stakeholders to translate data insights into product improvements. Manage end-to-end projects, establish quality standards, mentor junior staff, and drive continuous process improvement.

Leads complex data discovery, enrichment, curation, and AI-driven research initiatives. Develops data pipelines, enrichment models, taxonomies, ontologies, knowledge graphs, and intelligent workflows. Partners with product teams and customers to translate insights into product improvements, manages end-to-end projects, establishes quality standards, mentors junior colleagues, and drives continuous process improvement.

Analyzes operational data, validates data quality, develops dashboards and KPIs, reports performance metrics, identifies organizational risks, and presents actionable insights to internal and sponsor stakeholders. The role requires independent critical thinking, accurate data outputs, strong communication, and proficiency with Excel, Python, Power BI, PowerApps, Power Query, Power Pivot, and Power Automate.

Performs data administration, analysis, maintenance, quality management, database management, and report preparation. Applies analytical tools and professional judgment to interpret information, support business decisions, manage routine outputs, and identify or escalate compliance and control issues. Collaborates with related teams while developing broader knowledge of data management practices.