Top Data Analyst Jobs in Chennai

Design, build, and maintain Salesforce reports, CRMA dashboards, and Power BI migrations. Support data governance, monitor data quality, partner with CRM and engineering teams, and translate business requirements into scalable analytics solutions for Sales, Marketing, Operations, Finance, and Support.

Lead SOX compliance and ICFR activities including internal controls design, risk assessment, audit coordination, governance reporting, operational effectiveness, and stakeholder communication.

Design, build, test, deploy, and support HL7 interfaces and integration solutions. Analyze exchange requirements, troubleshoot interfaces, document work, participate in project calls, handle go-lives, and perform ongoing maintenance and provider enrollments. Provide on-call support in a 24/7 environment.

Partner with business lines and Risk/Compliance/Audit to design and maintain risk management frameworks, ensure regulatory compliance, identify process gaps, escalate risks, and act as liaison between business and lines of defense. Participate in projects to minimize losses from inadequate processes, systems, or human error.

Lead delivery of healthcare analytics solutions by transforming complex claims, clinical, and population health data into dashboards, reports, and actionable insights. Partner with clients and cross-functional teams to design use cases, implement analytics, manage adoption, ensure data governance, and support AI/ML and post-launch optimization.

Perform gap analyses across trading data from multiple source systems, identify discrepancies, build automated reports using Python and SQL, create visualizations (Power BI or Python libraries), present findings to stakeholders, and coordinate with upstream/downstream teams to implement logic and document requirements.

Perform sourcing-focused data analysis and reporting to support negotiations and supplier reviews. Build and validate datasets, identify cost drivers and pricing trends, create ad-hoc and recurring reports, collaborate with Category Management, Supply Chain, and Insights, and drive process improvements.

Develop, validate, and maintain analytics, reporting, and reusable data assets for product safety, quality, regulatory, clinical, and operational functions in a regulated medical device environment. Build scalable data pipelines and semantic models using Azure technologies, SQL, and Python; perform data validation and QA; produce audit-ready documentation and regulatory-compliant analytical outputs. Collaborate with cross-functional stakeholders to translate requirements into validated reporting solutions.

Implement, maintain, and support HL7 interfaces between customers and Optum integration platforms. Analyze requirements, design, build, test, document, deploy, and troubleshoot interfaces; perform maintenance, provider enrollments, validation, go-live support, and customer interaction. Participate in project meetings and on-call rotation.

Gather and process data, conduct trend analyses, develop statistical models, and identify insights to support advertising and media planning efforts.

The ERP Data Analyst is responsible for managing data deliverables, supporting ERP integrations, ensuring data quality, and enabling analytics, focusing on enterprise data transformation.

Design, build, test, deploy, and maintain scalable Azure-based data pipelines and integrations for healthcare analytics. Lead data acquisition, ETL/ELT transformations, data quality detection and remediation, monitoring, documentation, and collaboration with analytics teams to enable BI and advanced analytics while ensuring security and reliability.

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.

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.

Support design, development and rollout of data governance capabilities. Gather requirements, write user stories, prioritize backlog, analyze metadata and onboard datasets to governance platforms like Soda and Collibra.

Ensure reliability, scalability, and performance of the enterprise data platform. Automate IaC, CI/CD, and deployments; manage observability, governance, FinOps, and incident response; collaborate with engineering and analytics teams to improve platform reliability and developer experience.

Lead complex analytics for global complaint vigilance: perform trend and risk analyses, build dashboards, support data ingestion and data-lake strategy, present findings to QA and cross-functional partners, and enable corrective action and regulatory responses.

Label and validate datasets (documents, images, video, audio) for document fraud, deepfake, PAD, and face recognition. Create bounding boxes, landmarks, time-based frame labels, and flag tampering. Document edge cases, review peer annotations, ensure quality standards, and collaborate with ML engineers to improve datasets and tools.

The role involves data analytics with a focus on querying large data sets, visualization using Tableau, and applying quantitative skills, predominantly in the FMCG and Food & Distribution sectors.

The Data Analyst prepares, analyzes, and validates data, applying statistical methods and visualization techniques to derive insights and support business objectives. Communicates findings effectively and collaborates with Data Engineers for model and dashboard implementation.

Design, build, and maintain cross-vendor market data pipelines and QA processes. Investigate complex data issues, handle escalations, collaborate with product and engineering via JIRA, and ensure data accuracy for equities fundamentals, estimates, and market data.

Gather, clean, and analyze data from multiple sources; build and maintain Power BI and Excel dashboards; run SQL queries and Python scripts for automation; collaborate with cross-functional teams to interpret trends and communicate insights; create documentation and improve reporting processes.

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.

Perform exploratory analysis, build dashboards and reports (Tableau), write SQL queries, use Python for data cleaning and predictive models, collaborate with stakeholders, communicate insights, and maintain data models, pipelines, and quality checks.

Perform full-stack on-chain and product analytics: query on-chain data, profile ecosystem actors, benchmark protocols, define KPIs, build dashboards, and translate findings into actionable briefs for strategy, BD, product, and growth teams.