Top Data Analyst Jobs in Chennai

Independently leads data analytics and business intelligence initiatives, combining complex data sources to generate actionable insights. Performs exploratory analysis, hypothesis testing, forecasting, and LLM model development. Communicates findings through executive presentations and data visualizations while ensuring data integrity and compliance. Partners with business stakeholders to define technical requirements and applies emerging analytics, statistics, and machine learning techniques to business challenges.

The Talent Acquisition Business Analyst owns recruiting dashboards, reports, data analysis, data governance, and cross-functional process and systems improvement projects. The role translates stakeholder needs into reporting and workflow enhancements, uses AI to automate recruiting insights and processes, analyzes funnel and pipeline performance, and presents recommendations to recruiting leaders. Responsibilities include maintaining data quality, managing projects independently, and improving operational efficiency and stakeholder experience.

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

Leads advanced analytics and machine learning initiatives across sales, vendor management, cloud, eCommerce, finance, and supply chain. Develops predictive models, translates complex data into actionable business recommendations, scopes analytical workstreams, partners with stakeholders, and communicates insights to executives and technical teams. Requires strong SQL, Python, visualization, cloud, modeling, and business communication skills.

Supports liquidity regulatory reporting controls by documenting data flows, business data elements, lineage, transformations, and controls from booking systems to reporting platforms. Performs SQL-based data analysis, test-case development, functional and business testing, quality remediation, root-cause analysis, requirements management, stakeholder coordination, and management reporting. Contributes to implementation activities, change control, documentation standards, and training junior team members.

Leads enterprise data engineering, warehousing, analytics, reporting, and regulatory data initiatives for banking and financial services. Designs data platforms and pipelines, develops Oracle SQL and PL/SQL solutions, builds dashboards and reporting frameworks, and ensures data quality, governance, reconciliation, and lineage. Supports lending, risk, securities, tax, payments, treasury, and customer data management. Provides production support, incident resolution, root-cause analysis, and stakeholder collaboration across business, risk, finance, compliance, and technology teams.

Execute high-volume SAP procurement master data cleansing across info records, source lists, vendor masters, pricing, and contracts. Resolve cross-domain data defects, maintain source-to-pay alignment, operate mass-maintenance tools, track procurement defect and KPI metrics, complete exit-gate checklists, and transition cleared remediation patterns to business-as-usual teams. Collaborate with Procurement, Sourcing, Engineering, and Material Master specialists to resolve complex material, vendor, pricing, and contract issues.

Manage, clean, validate, and maintain programme datasets; analyze trends and performance gaps; develop dashboards, trackers, and reports; support monitoring and evaluation; and improve data collection workflows. The role provides actionable insights to state leadership and supports reviews with government and internal stakeholders. It requires strong Google Sheets and Excel skills, with visualization and SQL knowledge preferred, plus Tamil reading and writing proficiency.

Internship data analyst supporting dashboard monitoring, user behavior and content ecosystem analysis, A/B test evaluation, campaign performance analysis, data quality assurance, and metric documentation. The role uses SQL and Excel to derive insights on engagement, retention, conversion, and creator ecosystems, while collaborating with product and operations teams in a blockchain and digital assets environment.

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.

Support Finance and Central Operations by building dashboards, reporting, automated data pipelines, reconciliations, controls, and analytics. Analyze revenue, expenses, margins, cash flows, payment volumes, disputes, exceptions, and processing performance. Partner with Finance and Payment Operations to investigate discrepancies, automate workflows, improve data quality, and translate business questions into reliable models and actionable insights.

Migrate Adobe Analytics reports to Customer Journey Analytics, build clickstream and marketing dashboards, configure dataviews, validate Databricks data, and support experimentation analytics. The role develops Power BI reporting, performs SQL-based pre/post migration QA, documents reporting logic, and enables self-service analytics for marketing and product stakeholders across international markets.

Develop and deliver AI/ML solutions by building supervised and unsupervised models, deep learning systems, NLP and LLM applications. Responsibilities include LLM fine-tuning, prompt engineering, RAG, vector databases, transformer architectures, and AI agent deployment. The role requires partnering with business stakeholders, presenting technical findings, and continuously learning emerging AI technologies.

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.

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.

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.

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

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

Deliver complex analytics using Databricks, Snowflake, SQL, and Python to analyze large datasets, validate data products, assess model precision/recall, and present actionable insights to Product Owners and Data Scientists. Support data preparation, quality assurance, stakeholder communication, and continuous improvement of data products.

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.

Independently perform complex analytics and large-scale data preparation using Databricks, Snowflake, SQL, Python and Spark. Collaborate with Product Owners and Data Scientists to validate data products, evaluate model precision/recall, produce insights and recommendations, and communicate findings to stakeholders. Ensure data quality and support product improvements.

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.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Develops analytics, reporting assets, data pipelines, and automated solutions to improve credit and collections decisions. Analyzes customer and debt performance, identifies trends and root causes, evaluates initiatives, and translates findings into practical recommendations. The role also maintains data quality, governance, documentation, and analytical standards while partnering with Credit and Affordability stakeholders.

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.