Top Data Analyst Jobs in Delhi

The Senior Data Analyst will define source data, create data mapping, report inconsistencies, assist with data migration, and manage stakeholder expectations while delivering insights in financial services.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

The role involves building scalable data models, automating reporting, implementing metrics, developing dashboards, and ensuring data quality across teams globally.

Support development and maintenance of SQL-based data pipelines and analytics workflows. Assist data standardization, build and optimize data models, dashboards, and reports. Perform ad-hoc analyses, monitor data quality, implement validation logic, and collaborate on cross-functional data and risk projects under mentorship.

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.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Lead the data solutions strategy for PR&C PSP division, managing data initiatives, teams, and collaborating on analytics projects. Ensure compliance, governance, and optimize data services while communicating technical solutions to stakeholders.

Monitor and validate market data deliveries, batch processes, and feeds for SaaS clients. Troubleshoot data quality and technical issues, manage incidents, coordinate releases and production patches, and support API-related client queries. Develop standard operating procedures, automate manual checks using Python, engage vendors, and lead post-mortem and root-cause analysis activities. The role requires financial markets knowledge, especially derivatives and multiple asset classes, along with Excel, SQL, troubleshooting, and communication skills.

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

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

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.

Drive HR Data Governance by implementing metadata management, data lineage, data quality processes, and data access controls. Lead stakeholder engagement, run governance forums, track KPIs, and deliver the HR Data Governance roadmap to improve data trust and usability.

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.

Ensure accuracy, completeness, and integrity of Salesforce customer and account data. Build automated validation and enrichment pipelines (SQL/Python), perform large-scale cleansing and deduplication (DemandTools, Data Loader), create monitoring dashboards (Power BI), enforce governance, and apply AI/LLMs to improve matching, classification, and anomaly detection so data never blocks Quote-to-Cash processes.

Lead insider risk and data loss investigations from triage to closure, operate and tune DLP across environments, build detections and workflows, partner with HR/Legal/Compliance/IT, mature insider risk program, support audits, and mentor others.

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.

Lead the Data Desk: triage and route L1/L2 requests, perform code reviews for junior analysts, drive automation and self-service dashboards, run daily operations and people development, and ensure data quality and SLA adherence.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.

Ensure accuracy, completeness, and consistency of product data by validating, cleansing, enriching, profiling, and monitoring quality. Maintain data dictionaries, lineage, metadata, governance policies, dashboards, and compliance. Collaborate with stakeholders, operations, and other data stewards; train users and gather feedback to improve data products.

Ensure accuracy, completeness, and consistency of product data by validating, cleansing, profiling, and enriching content. Define data quality standards, maintain data dictionaries and lineage, implement governance policies, build quality dashboards, collaborate with stakeholders and operations, train users, and ensure compliance with privacy and regulatory requirements.

The Data Analyst will analyze marketing and ecommerce data, build reporting, dashboards, and KPIs, and enhance marketing attribution modeling.