Top Data Analyst Jobs in Mumbai

Operate, maintain and update data pipelines that validate, transform and enrich policyholder data for actuarial modelling. Investigate and resolve data issues, apply validations and governance, produce reports and dashboards, support audits, maintain documentation and data dictionaries, and work with stakeholders to translate requirements into transformation logic and code.

Collect, verify, and maintain corporate governance and compensation data for assigned markets; respond to internal/client queries, follow methodology and quality standards, meet turnaround goals, escalate and analyze data issues, update performance metrics, and support projects.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

Provide operational support for fund, product, index, and account reference data. Manage data ingestion, distribution, reconciliation, reporting, issue resolution, documentation, and vendor/stakeholder coordination while supporting data systems and corporate initiatives.

Analyze video to create and maintain high-quality labeled "golden sets" for ML, timestamp significant events, add detailed metadata, audit model outputs for errors, and collaborate with data scientists, engineers, and product teams to refine content descriptions for AI-driven media products.

The role involves analyzing data to drive strategic decisions and improve employee benefits services. Requires strong analytical skills and experience in data science.

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.

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.

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.

Lead enterprise data governance efforts for ERM: perform lineage assessments, identify and catalogue Critical Data Elements, define data quality rules, document endpoints and transformations, drive policy and risk/control frameworks, coordinate projects, and influence senior stakeholders to implement data governance standards and controls.

The Data Analyst will support product marketing initiatives by analyzing data, tracking KPI progress, developing dashboards, and providing actionable insights to inform decision-making across business units.

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 large datasets, build and maintain dashboards and reports, develop data models and KPIs, support forecasting and performance tracking, ensure data integrity, automate reporting, and present actionable insights to stakeholders.

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.

Lead finance analytics initiatives by partnering with stakeholders, analyzing large datasets (SQL/BigQuery), delivering ad hoc and dashboard-driven insights (Tableau/Power BI), automating reporting, and driving process improvements to support executive decision-making.

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

The Senior Director Analyst develops insights on data management platforms, leads the research agenda, engages clients, and mentors junior analysts, utilizing extensive expertise in data management and AI solutions.

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.

Maintain and operationalize the companys data governance artifacts: author and version taxonomies, business glossary terms, and data rules; detect and resolve rule conflicts and gaps; manage metadata and change history; support intake and certification of reference data; produce documentation and governance reporting to ensure rules are usable in production classification and quality workflows.

Design, develop, and support analytics solutions including dashboards, reports, and data models. Clean and transform data, ensure data quality and governance, partner with stakeholders to gather requirements, apply AI prompting/tools to accelerate delivery, and implement process and change improvements for scalable, production-ready analytics.

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.

Lead end-to-end data analysis: transform raw data, develop reports and dashboards (PowerBI), monitor performance and quality, implement ETL and data modeling, apply predictive modeling/NLP/machine learning, and support cross-functional data-driven decisions.