Top Data Analyst Jobs in Gurgaon

The Senior Analyst will execute Mastercard's Master Data Management strategy, ensuring data integrity and collaboration across enterprise systems and stakeholders while leading MDM initiatives and governance practices.

Leads data analytics, engineering, reporting, visualization, and modeling initiatives across products, markets, and services. Builds dashboards, semantic models, performance metrics, and data quality controls using large-scale data technologies. Delivers actionable insights and executive-ready recommendations to cross-functional stakeholders, leads strategic analytical projects, and mentors or supervises junior analysts and data engineering talent.

Entry-level Product Data Analyst internship supporting product analytics: build and analyze conversion funnels, evaluate A/B tests, create dashboards, respond to ad-hoc data requests, write SQL pipelines, monitor data quality, and translate findings into visual summaries to inform product decisions.

Lead Data Analyst responsible for translating business requirements into analytical solutions, performing A/B and sales funnel analyses, building reports and automations, managing intake/prioritization, documenting processes, coordinating with stakeholders, and delivering actionable insights to support reporting, model validation, and operations.

Lead Data Analyst responsible for managing intake and prioritization, translating business requirements into analytical solutions, performing A/B test and sales funnel analyses, developing and automating reports using Python and SQL, documenting processes, coordinating with US and internal teams, and delivering actionable insights to drive product and process improvements.

Lead analytics projects to improve client retention across content, interactions, and events. Analyze large datasets, partner with data scientists and engineers to build scalable solutions, automate reporting, and present insights to business leaders. Own problem structuring, stakeholder engagement, and deliver cross-organizational analytics.

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.

Analyze and interpret large healthcare datasets, build and maintain data pipelines and structures, collaborate with cross-functional teams to deliver actionable insights, and document data processes and analyses.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

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.

Own business data requests, build and optimize Power BI dashboards, automate recurring reporting, and deliver ad hoc analyses. Translate ambiguous business questions into actionable insights, define and track KPIs, ensure data quality, and support decisions through visualization and storytelling. The role partners with Product, Brand, Marketing, Operations, and executive stakeholders while independently managing priorities and service-level expectations.

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.

Collect, clean, and analyze large datasets; perform statistical analysis; create reports and dashboards; and collaborate with stakeholders to deliver data-driven insights that support business decision-making.

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.

Analyze investment and accounting data supporting Asia data modernization and IBOR/ABOR initiatives. Define data requirements, business rules, governance artifacts, and quality checks; perform reconciliations and root-cause analysis; validate Power BI and enterprise reporting datasets; and translate business needs for engineering, BI, product, investment, finance, and risk stakeholders.

Build and maintain BI and analytics solutions, delivering interactive Power BI dashboards and reports. Translate business requirements into data models, SQL-based solutions, and actionable marketing analytics insights. Serve client-facing stakeholders across end-to-end BI development, data warehousing, and reporting.

The Data Analyst will collect, clean, and analyze data, design advanced models, support strategic projects, and communicate findings within biopharmaceutical contexts.

Own strategic analytics initiatives supporting client retention and business performance. Analyze large datasets, identify trends, develop actionable insights, and partner with data science and engineering teams on scalable analytics solutions. Engage business leaders to understand challenges, structure problems, and deliver solutions. Present findings to senior stakeholders while applying statistical methods, data-quality practices, visualization, and foundational data science concepts.

Support data collection, cleaning, preprocessing, analysis, and reporting. Assist in creating data models and reports to inform business decision-making.

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 complex data analysis projects: collect, clean, and analyze large datasets; create dashboards; develop predictive models; and deliver actionable insights to business stakeholders to support decision-making.

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.

Implement and maintain SQL and Power BI solutions; translate business needs into data tasks; ensure data quality and validation; create data models and semantic layers; build client-ready dashboards and reports; automate workflows using Power Apps and Power Automate; liaise with stakeholders to define reporting requirements.

Serve as liaison between business and technical teams to gather requirements, profile and standardize data, perform data mapping, transformations and consolidation, document data lineage and models, and support insurance (P&C) policy, claims and reinsurance data initiatives.