Top Data Analyst Jobs in Gurgaon

Analyze, clean, transform, and interpret data from multiple sources to identify trends and actionable insights. Build and maintain SQL queries, dashboards, reports, and visualizations for business and operational metrics. Support KPI definition, exploratory analysis, anomaly investigation, reporting automation, and data-quality initiatives while collaborating with business, engineering, and technical stakeholders.

Supports client analytics initiatives through exploratory analysis, dashboard and report development, KPI tracking, data quality validation, metric documentation, and visualization. Collaborates with engineers, analysts, product teams, designers, and stakeholders to translate business questions into analytical requirements and communicate insights. The role also develops consulting skills across digital products, transformation, UX, and design thinking.

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 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.

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.

Build and manage financial data models, pipelines, Power BI dashboards, DAX measures, and automated reporting solutions using Microsoft Fabric and Dynamics 365. Support FP&A through KPI tracking, monthly reporting, scenario analysis, and decision support. Collaborate with finance, IT, and data teams to ensure data quality, governance, documentation, and a trusted source of financial information for business stakeholders.

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.

Analyzes trade, shipment, ERP, logistics, and landed-cost data to support global trade compliance. Builds dashboards, scorecards, recurring reports, and digital tools using SQL, Power BI, Tableau, Python, and related technologies. Supports data quality, origin and free trade agreement analyses, duty optimization, trade-flow monitoring, and risk identification. Collaborates with Trade, Supply Chain, Procurement, Finance, IT, and business teams to deliver reliable, audit-ready insights and scalable compliance solutions.

The HRIS Data Analyst develops advanced HR reports, dashboards, visualizations, and workforce insights using UKG, IBM Cognos Analytics, Power BI, and Excel. The role analyzes HR, compensation, turnover, compliance, and operational data; translates business needs into reporting solutions; validates data quality; and partners with HR Business Partners and HRIS teams. This senior individual contributor also supports reporting standards, process improvements, documentation, and strategic HR decision-making.

Lead data analysis and reporting operations by managing intake and prioritization, translating business requirements into analytical solutions, conducting A/B testing and sales funnel analysis, and delivering actionable insights. The role develops complex reports, automates report distribution, supports model validation, applies econometric methods, documents processes, and communicates recommendations to US and internal stakeholders using Python, SQL, and reporting tools.

Leads reporting and data analytics initiatives, including intake prioritization, A/B testing, sales funnel analysis, ad hoc business analysis, reporting automation, and model validation. Translates business requirements into analytical solutions, communicates insights to stakeholders, and supports process improvements. The role requires Python, SQL, RDBMS expertise, complex query development, documentation, and independent collaboration with global teams.

Analyze company-wide revenue and operational metrics, develop recurring consumption and revenue reports, conduct root-cause analyses, and provide executive-level insights. The role partners with Analytics, FP&A, Accounting, Cloud Billing, and Sales Operations; maintains data pipelines and visualizations; resolves data quality issues; and documents metric definitions, reporting logic, and data lineage. It requires strong SQL, Python, BI, and automation skills, with experience owning business metrics reporting.

Support EMEA Distribution by transforming client data, delivering commercial insights, building stakeholder relationships, driving data governance, automating processes, and developing AI-enabled analytics to improve decision-making and productivity.

Support EMEA Distribution by transforming and governing client data, delivering analytics and AI/automation initiatives, generating commercial insights, forecasting, and engaging stakeholders to prioritise and implement high-impact data solutions.

Analyze courier supply and dispatch operations across onboarding, retention, availability, earnings, assignment, acceptance, and delivery success. Build reliable metrics, dashboards, and self-service reporting; identify root causes of performance changes; evaluate experiments, incentives, and product initiatives; validate data quality; and translate findings into recommendations for product, operations, and leadership.

Build and optimize procurement data pipelines, ETL/ELT workflows, data models, curated datasets, dashboards, APIs, and automation. Partner with stakeholders to translate analytics needs into technical requirements and deliver end-to-end data products. Implement data quality, governance, documentation, and production support practices while improving solution performance, reliability, and cost. Collaborate on architecture, code reviews, technical standards, and continuous improvements across the data platform.

Build and optimize cloud-based data pipelines, ETL/ELT workflows, data models, curated datasets, APIs, and automation for procurement analytics. Partner with stakeholders to define requirements, develop reporting solutions, monitor data quality, support governance, and improve the performance, reliability, and cost of production data systems.

Owns the integration, quality, migration, and analysis of energy, utility, and smart-building data across JLL’s JouLLe platform. Responsibilities include data validation, utility reporting, tariff and budget analysis, platform administration, requirements gathering, system implementation, vendor coordination, project delivery, dashboard management, client training, audits, and process automation.

Analyze marketing data to measure campaign performance, ROI, attribution, customer behavior, and funnel conversion. Build Tableau dashboards and reports, define KPIs and measurement frameworks, evaluate experiments, and provide recommendations for campaign strategy and budget allocation. Translate complex findings into executive-ready presentations and collaborate with global marketing stakeholders across digital, social, email, and event channels.

Owns McCain’s global data retention, archiving, disposal, and legal hold framework. Leads SAP ILM and S/4HANA archiving, governs Databricks data lifecycle controls, develops retention schedules, manages compliance requirements, and partners with Legal, Privacy, Compliance, SAP, and business teams. The role also oversees storage tiering, risk registers, governance standards, operational performance, and cost and risk reduction initiatives.

Ensures inbound client and supplier data is complete, accurate, and report-ready. Provides Level 2 support for post-travel data issues, performs root-cause analysis, coordinates with technical, product, back-office, vendor, and internal teams, and identifies process improvements and automation opportunities. The role requires maintaining quality and compliance standards, meeting SLAs, and working rotational shifts.

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 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.

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.