Top Data Analyst Jobs in Gurgaon

Collect and validate quantitative and qualitative cargo/freight data from primary sources and web tools, reconcile discrepancies, maintain data quality, produce automated reports and daily summaries, and generate targeted prospect lists to support sales teams while meeting weekly deadlines.

Partner with EMEA Distribution to deliver data-driven commercial insights, build and maintain dashboards and automated reports, perform advanced analytics (trend analysis, forecasting), and collaborate with stakeholders to prioritize and deliver high-impact solutions.

Design, develop, and support dashboards, reports, and data models; prepare and transform data; ensure data quality and governance; partner with stakeholders to deliver end-to-end analytics solutions and drive process improvement.

Design, develop, and maintain data pipelines and Snowflake-based warehouses; perform complex analysis with SQL and Python; integrate data across systems and front-end/reporting applications; ensure data quality and governance; collaborate with stakeholders and document transformation logic and data workflows.

Lead analytics workstreams for life sciences clients, design and execute commercial and real-world data analyses, build dashboards and visualizations, apply statistical and machine learning methods, and communicate insights to clients and stakeholders.

Lead data analysis workstreams using large datasets and AWS analytics tools to define metrics, test hypotheses, perform root-cause analysis, produce insights and visualizations, and present actionable recommendations to stakeholders.

The role involves supporting and maintaining the Azure Data Platform by managing incidents, monitoring performance, and optimizing database operations. Responsibilities include troubleshooting ADF, Synapse Analytics, and ensuring data security compliance.

The Data Operations Analyst will enhance operational efficiency through data analysis, create dashboards, automate processes, and maintain data quality in collaboration with stakeholders.

The Senior Analyst will lead analytics engagements, transforming business problems into structured solutions. Responsibilities include data analysis, developing insights, and supporting dashboard efforts while leveraging emerging technologies.

Support investment reference data for public and private assets: daily asset setup, EOD pricing and QC, reconciliation on Duco/Sigma, SQL-based ad hoc analysis, SOP documentation, and process automation to improve efficiency.

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

The Analyst will lead data analytics for Direct Mail campaigns, driving acquisitions through optimization and machine learning solutions while collaborating with cross-functional teams to meet revenue goals.

Manage data cataloging, classification, master data mappings, and data quality for the actuarial department. Enforce compliance (GDPR/HIPAA/insurance regs), run audits, lead governance projects, train stakeholders on Alation/Excel, and collaborate with IT, data owners, and business leaders to ensure data discoverability and integrity.

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.

Design, write, and execute test plans and automated scripts to validate data across platforms (Datorama/Power BI) and source systems. Use SQL, Excel, and Python for data analysis, testing, and validation. Monitor QA metrics, mentor junior QA staff, document processes, and drive continuous improvement in QA standards and automation.

The role involves data management, transformation, analysis, and visualization, focusing on tool implementation and monitoring. Tasks include data integration, pipeline management, exploratory analysis, business reporting, KPI tracking, and data storytelling.

The Quality Analyst will research, validate, and maintain data records in Zendai, ensuring accuracy and consistency of information. Responsibilities include auditing projects, managing duplicates, and providing data quality support across global teams using MS-Excel.

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.

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.