Top Data Analyst Jobs in Gurgaon

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.

Design, build, and operate scalable ETL/ELT data pipelines and curated datasets on Hadoop/cloud platforms. Optimize performance, ensure data quality, lineage, and governance, enable analytics and ML-ready datasets, support CI/CD for data workflows, troubleshoot production issues, and collaborate with product, data science, and platform teams.

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.

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.

Build and maintain Power BI dashboards and predictive forecasting models that transform cloud and on‑prem infrastructure metrics into actionable capacity-planning insights. Query and blend data from billing, monitoring tools and APIs, forecast resource demand, monitor KPIs, identify risks, and produce executive reports to guide optimization and cloud spend.

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.

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.

Analyze and interpret business data, create dashboards and reports, clean and transform datasets, maintain databases, automate reporting with Excel VBA and SQL, identify trends, and provide ad hoc insights to management. The role also supports process improvement, data architecture, and cross-functional business decision-making.

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

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.

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.

Early-career platform engineer supporting development and maintenance of cloud infrastructure. Support automation of deployments, monitoring, and scaling; troubleshoot with senior engineers; apply DevOps practices; document configurations and participate in code reviews and team learning.

Validate datasets and tables produced by upstream data teams using SQL. Perform table-level source vs output checks, identify data anomalies, drive issue resolution, and collaborate with data teams to confirm expected outputs and business logic.

Design, build, and maintain scalable data pipelines and semantic data models in dbt and Snowflake. Profile and ingest client data, implement data quality testing and version control, and enable self-service analytics via Tableau. Collaborate with stakeholders to deliver reporting and analytic solutions, and support ML/NLP initiatives.

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 large-scale transactional, operational, and customer datasets; build visualizations, machine learning models, and experiments; translate complex findings into clear recommendations for operational teams and executives; and apply analytical software, databases, visualization tools, and programming languages in a fast-paced blockchain environment.

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.

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.