Top Data Analyst Jobs in Pune

Leads data analytics for Financial Crime Agile Testing, defining hypotheses, testing plans, data requirements, and analytical approaches. Oversees SQL, Python, and SAS analytics, quality-controls scripts and outputs, evaluates data quality and control effectiveness, and communicates findings to stakeholders. Provides technical guidance and escalation support to analysts, contributes to methodology improvements, and ensures independent, risk-based, reproducible testing with appropriate documentation, evidence retention, and data-privacy compliance.

Designs and maintains Power BI dashboards and reports, builds Power Apps applications, gathers business requirements, develops data models and visualizations, and performs data analysis. The role ensures data quality and integrity, supports data integration and automation through Microsoft Power Platform tools, and collaborates with stakeholders to translate business needs into actionable insights. Process mining experience is preferred for identifying inefficiencies and recommending improvements.

Configures and maintains global Empower CDS master data, including Custom Fields, Report Methods, View Filters, and laboratory method configurations. Translates analytical requirements into compliant technical designs, manages change control and SDLC activities, performs validation testing, supports LabWare LIMS integrations, and investigates configuration issues. The role also drives data standardization, performs second-person reviews, and collaborates with global laboratory, validation, and technical teams in a regulated pharmaceutical environment.

Supports financial reporting and analytics by performing ad hoc data analysis, validating month-end reports, monitoring reporting systems, resolving data issues, and meeting SLA commitments. The role supports SAP Analytics Cloud reporting, budget processes, data integration, automation, and stakeholder communication. It requires strong financial reporting knowledge, analytical skills, and experience with tools such as Databricks, Python, Power BI, and BW4.

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.

Analyze and improve data quality, lineage, controls, and authoritative sources. Build data pipelines, logical data models, dashboards, reports, and automated analytics. Apply statistical, machine learning, and advanced analytical techniques to identify trends, risks, anomalies, and improvement opportunities. Translate complex findings into actionable recommendations for senior stakeholders while ensuring data governance, privacy, security, regulatory compliance, and reporting accuracy. Partner across business, technology, risk, finance, operations, and data teams, potentially leading analytical workstreams.

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.

Extracts, transforms, and analyzes data to identify insights, conduct hypothesis testing, and support sales and client research initiatives. Manages custom analytics projects, presents findings, validates results, improves processes through automation, develops products and reporting tools, and mentors analysts. Collaborates across teams and supports media measurement offerings spanning digital, mobile, OTT, and television.

Supports sales-force effectiveness through data cleaning, access governance, KPI reporting, performance trend analysis, and migration from Excel tracking to Power BI dashboards. The role also provides user support, onboarding and training assistance, documentation, process standardization, and continuous improvement across regional sales entities.

Extracts, transforms, and analyzes media measurement data to identify insights, test hypotheses, and answer client and stakeholder questions. Leads data investigations, develops analytical solutions, supports sales feasibility reviews, and contributes to reporting tools and automation. Collaborates across teams, formulates technical approaches to open-ended problems, and improves analytical workflows using SQL, Python or R, ETL tools, cloud technologies, and Excel.

Analyze and interpret business data, support reporting and insights, and contribute to data-driven decision-making. The role is open to freshers and candidates with up to two years of experience, with opportunities to develop IT and analytical skills.

Manages and governs data assets by supporting data strategy, quality, standards, access, validation, standardization, protection, and publication. Works on limited-scope data management projects, follows established procedures, resolves routine technical issues, and supports trusted data use for regulatory and business goals. The role may require multiple shifts, including late-night shifts.

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.

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.

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.

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.