Top Data Analyst Jobs in Delhi

Develops and improves clinical site payment forecasting models, integrating enrollment, operational, and Medidata Payments data. Produces client-ready financial forecasts and reports, analyzes budget utilization and forecast variances, supports revenue recognition, audit compliance, and final payment reconciliations, and collaborates with Clinical Operations, Revenue Recognition, Project Analysis, and Clinical Payments teams across the study lifecycle.

Analyze homeowners insurance data to support pricing, underwriting, retention, product, and competitive intelligence decisions. Write SQL across BigQuery and SQL Server, build Power BI dashboards, identify portfolio trends and anomalies, measure product changes, and ensure data quality through QA and reconciliations. The role partners with product managers and business leaders, requiring autonomous problem-solving, clear communication, and cross-functional analysis.

Owns payroll implementation data by extracting, cleaning, mapping, loading, and reconciling employee, compensation, tax, benefits, and retirement data. Performs validation and audit checks, verifies deductions and contribution limits, documents variances, maintains loading records, and updates project and ticketing systems. Works with US implementation specialists to ensure accurate client onboarding and first payroll processing.

Conduct media, social listening, influencer, and predictive analytics research for agency clients. Manage recurring and ad hoc KPI reporting, trend analysis, crisis monitoring, and optimization recommendations. Translate data into strategic insights and compelling stories, advise account teams and leadership, and mentor junior analysts. Support consumer, technology, healthcare, and food and beverage accounts while using specialized social listening tools and Boolean queries.

Generates and manages accurate data for reports, oversees coding quality and junior coding teams, manages content searches and uploads, performs data checks, troubleshoots data-flow issues, creates charts and qualitative insights, and supports data exports, contact management, verification, and report production.

Analyze and integrate Salesforce data across CPQ and billing projects. Support enterprise-grade CPQ design and implementation across regions and billing systems, perform data gap analysis, manipulation, standardization, and large-dataset comparisons. Apply knowledge of subscriptions, order orchestration, activation, revenue recognition, invoicing, taxation, payments, general ledger processes, and the Salesforce CPQ data model.

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.

The Data Analyst develops and maintains Power BI dashboards, datasets, data models, SQL and DAX solutions, and data pipelines. The role supports AWS cloud analytics integration, data quality, troubleshooting, governance, documentation, and workspace administration. It coordinates data engineers, translates business requirements into technical deliverables, collaborates with stakeholders, and communicates findings to nontechnical audiences while supporting agile delivery and data privacy compliance.

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.

Own business data as a trusted source of truth by building metrics, dashboards, reporting systems, and analytical frameworks. Analyze complex datasets with advanced SQL, define KPIs, identify trends and opportunities, and solve ambiguous business problems. Partner with business, marketing, finance, and other teams to translate analysis into clear recommendations and data-driven decisions.

Build, maintain, and optimize enterprise data platforms using Databricks, Apache Spark, cloud technologies, and DevOps tools. Develop CI/CD pipelines, support cloud migration and automation, monitor platform health, resolve incidents, and ensure security, governance, reliability, and operational standards. Collaborate with engineers, architects, product teams, stakeholders, and global support teams while participating in rotational production support shifts.

Supports enterprise data platform engineering through Databricks and Spark workload management, cloud platform operations, CI/CD automation, monitoring, incident resolution, production support, and platform modernization. The role collaborates with engineering, architecture, product, and business teams while maintaining security, governance, reliability, documentation, and operational standards. Rotational shifts provide global support coverage.

Build and maintain OneStream forecasting, planning, reporting, and dashboard capabilities for Commercial FP&A. Develop demand planning models, reports, reconciliations, and performance monitoring processes while supporting month-end reporting and data improvement initiatives. Partner with finance, data, administration, and implementation teams to optimize the platform, automate processes, troubleshoot performance, deliver actionable insights, and develop internal OneStream expertise. The role also evaluates AI and automation opportunities across FP&A workflows.

Supports FOX corporate services and business intelligence platforms by analyzing data challenges, maintaining platforms, researching trends, preparing reports, assisting employees, and collaborating with cross-functional teams. The apprentice will develop technical and analytical skills through training, mentorship, and real-world projects while contributing insights that improve user experience and operational efficiency.

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.

Provide ad-hoc data and reporting support to Sales and internal teams using SQL, Databricks/Count, and spreadsheets. Clarify requirements, investigate discrepancies, resolve basic data issues, support routine data operations, and create reusable queries/reports and documentation to enable self-service.

Analyzes, transforms, validates, and manages SAP and business data in cloud environments. Develops reports, dashboards, and analytical solutions; performs data quality, cleansing, reconciliation, migration, and troubleshooting activities. Collaborates with business stakeholders and SAP functional and technical teams to define requirements, resolve reporting issues, document processes, and present actionable insights.

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.

Own analytics and measurement for HighLevel’s AI product portfolio. Define instrumentation standards, feature-level KPIs, adoption and quality metrics, and rigorous approaches for evaluating nondeterministic AI features. Partner with experimentation leaders, PMs, engineering, and Analytics Engineering to close data gaps, influence product roadmaps, establish canonical metrics, and mentor future analysts.

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.

Audits and validates labeling annotation data for accuracy, consistency, guideline adherence, and regulatory compliance. Identifies errors and root causes, monitors quality KPIs, leads governance cycles, translates data trends into process improvements, and leads the NC Program. Collaborates with agencies and internal stakeholders across labeling operations.

Own marketing database operations for EMEA, including audience segmentation, data quality, privacy compliance, and performance analysis. Translate complex marketing data into actionable insights, recurring reports, and segmentation models. Partner with Marketing Operations, IT, and Data teams to improve database accuracy and processes, while enabling stakeholders through clear communication and training. The role requires strong SQL, marketing technology, project ownership, and business-facing analytical skills.

Conduct a three-hour interactive online training session on qualitative data analysis, including thematic and content analysis, coding, codebook development, identifying themes, transcript and focus group analysis, practical case studies, and qualitative analysis tools.