Top Data Analyst Jobs in Chennai

Develops advanced analytics solutions to address complex business challenges, using data visualization to communicate insights and influence decisions. Partners with stakeholders to define opportunities, improve and automate processes, and deliver commercial and customer value. Leads colleagues, coordinates data analytics resources, supports strategic projects and scrum outcomes, and connects data science, data engineering, and analytics work. Requires strong data management, data architecture, coding, cloud, visualization, and analytics expertise.

Develops advanced analytics and data solutions to address business challenges, improve processes, and generate customer and commercial value. The role consults with stakeholders, defines analytical questions, creates meaningful visualizations, communicates insights, and coordinates multidisciplinary Agile data teams. It requires technical capability, cloud experience, data architecture knowledge, analytics tooling and coding knowledge, plus an understanding of financial services.

Leads a data and analytics team at vice president level, coaching colleagues and delivering strategic analytics solutions. Partners with stakeholders to define complex business questions, plans analytics resources, applies advanced analytics and visualization, and communicates insights to support business decisions. The role also requires knowledge of data architecture, cloud environments, coding, emerging tools, and methodologies, with a focus on customer and commercial impact.

Develops advanced analytics solutions to address complex business challenges and improve understanding of customers, processes, channels, and products. Consults with stakeholders, translates insights into visualizations, leads strategic projects and scrum outcomes, coaches colleagues, and connects data science and engineering work to business needs. Requires strong technical capability, cloud experience, data architecture knowledge, and the ability to communicate complex findings clearly.

Designs and maintains Microsoft Fabric data pipelines, Lakehouse and Warehouse solutions, layered data architectures, dimensional models, and scalable ETL/ELT processes. Develops SQL queries, Python transformation scripts, and data-quality validations using Pandas, NumPy, PySpark, and Requests. Builds Power BI-ready datasets, supports KPI and metric definitions, partners with stakeholders on analytics requirements, and promotes governance, lineage, performance, and reporting consistency.

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.

Analyze structured and unstructured data to identify trends, build dashboards and reports, define KPIs, validate data quality, and provide actionable recommendations. The role requires SQL, BI visualization, Excel, relational database experience, and collaboration with business and technical stakeholders. Preferred skills include Python, ETL and data warehousing, cloud platforms, statistical analysis, forecasting, machine learning concepts, and Agile experience.

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.

Leads a team of scientific data analysts supporting Reaxys, Embase, and future AI-enabled life sciences platforms. Oversees search and API quality, data discoverability, testing, feature releases, quality standards, and customer-focused insights. Uses scientific expertise, Python and Bash scripting, databases, cloud platforms, and AI-enabled testing workflows to improve data integrity and platform performance. Coordinates stakeholders, documents work, presents findings, and drives cross-functional projects.

Leads a team of scientific data analysts supporting Reaxys, Embase, and future AI-enabled life sciences platforms. Oversees search and API quality evaluation, data discoverability, testing, feature releases, customer-focused insights, and quality standards. Uses scientific expertise, data analysis, scripting, databases, cloud platforms, and AI-enabled testing workflows to improve platform reliability and relevance. Coordinates stakeholders, advances projects, documents work, and presents recommendations for product and data improvements.

Analyze CPG/FMCG data to support pricing, distribution, sales, revenue, and commercial decision-making. Develop and optimize Power BI dashboards, reporting solutions, and analytical models; identify trends, performance gaps, pricing and distribution opportunities; track KPIs; improve data quality; automate reporting; and present actionable recommendations to cross-functional stakeholders.

Own analytics and measurement for HighLevel’s AI product portfolio. Define instrumentation standards, feature-level KPIs, adoption and quality metrics, and rigorous approaches for evaluating nondeterministic AI features. Partner with experimentation leaders, PMs, engineering, and Analytics Engineering to close data gaps, influence product roadmaps, establish canonical metrics, and mentor future analysts.

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.

Evaluates, acquires, and manages external healthcare and pharmaceutical data sources for Roche’s U.S. commercial and strategic teams. Translates stakeholder needs into data requirements, assesses vendors and datasets for quality and business fit, investigates data issues, maintains documentation, and supports dataset onboarding and investment decisions. The role requires collaboration with U.S. stakeholders, external vendors, and cross-functional teams, along with structured analysis, stakeholder management, and knowledge of pharma and healthcare data ecosystems.

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.

Maintains vendor master records and new vendor setups, manages supplier transactions, resolves pricing and commercial terms with suppliers and buyer groups, provides reports and analysis, and supports internal stakeholders using ERP and office software.

Lead data science projects: analyze banking data, build ML solutions, design data displays, consult with stakeholders, manage requirements-to-implementation, coach junior staff, and ensure compliance and data quality.

Supports hosted e-discovery platforms by loading and transforming data, creating databases and user accounts, configuring permissions, investigating client technical inquiries, and assisting customers through phone, email, and screen sharing. The role also manages internal service-level tasks, collaborates with Engineering, IT, Application, and Project Management teams, and provides platform walkthroughs when needed.

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.

Conduct a three-hour interactive online training session on qualitative data analysis, including thematic and content analysis, coding, codebook development, identifying themes, transcript and focus group analysis, practical case studies, and qualitative analysis tools.

Supports data pipeline development and maintenance, performs foundational data engineering and processing tasks, follows data quality and security standards, and collaborates on data initiatives while developing expertise under senior guidance.

Supports platform operations and third-party partnerships by troubleshooting customer and integration issues, managing cases in Salesforce, improving procedures, documenting workflows, and coordinating resolutions with internal teams and external partners. The role communicates project updates and risks, identifies recurring issues, and contributes to process improvement, automation, and tooling initiatives. Strong SQL, communication, organization, and stakeholder management skills are required.

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.

Supports platform operations by troubleshooting customer and partner issues in Salesforce, coordinating resolutions, maintaining procedures, communicating project updates, and improving support workflows. The role works with HL7 connections, APIs, Data View, and other platform services while identifying recurring issues and opportunities for improved tooling, automation, documentation, and operational consistency.