Top Data Analyst Jobs in Chennai

Lead end-to-end reporting requirements, data definitions, integrations, and data models for global finance and operational reports. Bridge stakeholders, source systems, and Power BI team to ensure consistent KPIs, data quality, and single source of truth while defining integration specs, reconciliation rules, and governance.

Build reports and metrics to measure customer health and company performance, support stakeholders with ad hoc queries, enable self-serve analytics, document data, mentor peers, and shape analytics team processes.

Lead reporting and metric development to measure customer health and company performance, enable self-service analytics, provide ad-hoc query support, partner with stakeholders, document data, mentor peers, and help establish analytics culture and processes.

Perform data analysis, preprocessing, and modeling; collaborate with the data science team to generate reports and present findings; support project monitoring and resolve data challenges under senior guidance.

The Senior Analyst will own Pricing Tools, manage data governance, drive pricing strategy decisions, execute audits, and enhance operational effectiveness.

Design and execute test cases, plans, and strategies for ETL/data workflows. Perform functional, integration, and regression testing, validate backend data using SQL/Snowflake, read stored procedures, identify defects, support resolution with developers, and develop/maintain Python automation scripts and test documentation.

Elicit and document finance and risk business requirements, translate to functional specifications, collaborate with data and development teams, support regulatory compliance (Basel/IFRS/SOX/CCAR), validate data quality/lineage, participate in UAT, and prepare BRDs/FRDs and user documentation.

The Senior Data Analyst will leverage data to inform strategic decisions, analyze complex datasets, develop predictive models, and communicate insights to stakeholders.

Owner of company-wide reporting and analytics for Growth, Marketing, Product, Finance and Operations. Build and maintain dashboards, automated reports and data pipelines (dbt), ensure data quality and governance, run growth and product analyses (CAC, ROAS, LTV, retention), support A/B testing and ad-hoc decision support, leverage AI for automation, and coordinate VAs on data tasks.

Lead consolidation, validation and integrated reporting of project performance data across engineering, procurement, fabrication and project controls. Develop executive dashboards and advanced analytics (including Monte Carlo simulation and contingency analysis), support governance, and partner with multidisciplinary project teams on major EPC, LNG and energy infrastructure projects.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Ensure accuracy, completeness, and integrity of Salesforce customer and account data. Build automated validation and enrichment pipelines (SQL/Python), perform large-scale cleansing and deduplication (DemandTools, Data Loader), create monitoring dashboards (Power BI), enforce governance, and apply AI/LLMs to improve matching, classification, and anomaly detection so data never blocks Quote-to-Cash processes.

Lead insider risk and data loss investigations from triage to closure, operate and tune DLP across environments, build detections and workflows, partner with HR/Legal/Compliance/IT, mature insider risk program, support audits, and mentor others.

The role involves supporting and maintaining the Azure Data Platform by managing incidents, monitoring performance, and optimizing database operations. Responsibilities include troubleshooting ADF, Synapse Analytics, and ensuring data security compliance.

Lead the Data Desk: triage and route L1/L2 requests, perform code reviews for junior analysts, drive automation and self-service dashboards, run daily operations and people development, and ensure data quality and SLA adherence.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.

Ensure accuracy, completeness, and consistency of product data by validating, cleansing, enriching, profiling, and monitoring quality. Maintain data dictionaries, lineage, metadata, governance policies, dashboards, and compliance. Collaborate with stakeholders, operations, and other data stewards; train users and gather feedback to improve data products.

Ensure accuracy, completeness, and consistency of product data by validating, cleansing, profiling, and enriching content. Define data quality standards, maintain data dictionaries and lineage, implement governance policies, build quality dashboards, collaborate with stakeholders and operations, train users, and ensure compliance with privacy and regulatory requirements.

The Data Analyst will analyze marketing and ecommerce data, build reporting, dashboards, and KPIs, and enhance marketing attribution modeling.