Top Data Analyst Jobs in Pune

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.

Provides L1 production support for financial applications and enterprise data platforms. Responsibilities include monitoring ETL jobs, data pipelines, batch schedules, alerts, and incidents; troubleshooting data quality, reconciliation, ingestion, reporting, and application issues; performing SQL-based data updates, smoke testing, root-cause analysis, and impact assessment; coordinating with technical and business teams; escalating complex issues; supporting disaster recovery, audits, automation, and continuous service improvement.

Supports enterprise data platform design, maintenance, monitoring, and production operations. Develops Databricks and Spark workloads, maintains CI/CD pipelines, supports cloud migration and automation, investigates incidents, and contributes to platform reliability, security, governance, documentation, and continuous improvement. The role operates on rotational shifts and collaborates with globally distributed engineering, product, architecture, and business teams.

Build, maintain, and optimize enterprise data platforms using Databricks, Spark, cloud technologies, and DevOps practices. Develop CI/CD pipelines, support cloud migration and automation, monitor platform health, troubleshoot incidents, and ensure reliable, secure, and scalable data services. Participate in rotational production support across global time zones, perform root cause analysis, maintain operational documentation, and collaborate with engineering, architecture, product, and business teams.

Lead oncology patient-journey, line-of-therapy, brand, HEOR, and healthcare resource utilization analytics using structured claims and patient data. Build SQL pipelines, perform exploratory and statistical analyses, ensure data governance and reproducibility, and translate findings into dashboards and client-facing insights. Collaborate with HEOR, market access, strategy, and engineering teams while independently managing project delivery and stakeholder communication.

Lead oncology analytics projects involving patient journeys, line-of-therapy mapping, claims data, brand analytics, and HEOR/HCRU studies. Build SQL pipelines and use Python and Excel to analyze structured healthcare datasets, ensure data integrity, and deliver reproducible insights. Develop dashboards and client presentations while collaborating with HEOR, market access, strategy, and engineering teams. Independently manage project delivery and stakeholder communication.

Support Finance and Central Operations by building dashboards, reporting, automated data pipelines, reconciliations, controls, and analytics. Analyze revenue, expenses, margins, cash flows, payment volumes, disputes, exceptions, and processing performance. Partner with Finance and Payment Operations to investigate discrepancies, automate workflows, improve data quality, and translate business questions into reliable models and actionable insights.

Develop and deliver AI/ML solutions by building supervised and unsupervised models, deep learning systems, NLP and LLM applications. Responsibilities include LLM fine-tuning, prompt engineering, RAG, vector databases, transformer architectures, and AI agent deployment. The role requires partnering with business stakeholders, presenting technical findings, and continuously learning emerging AI technologies.

Build and maintain internal business intelligence dashboards covering revenue, profitability, headcount costs, and team utilization. Support leadership, Finance, and HR with ad hoc analysis and planning insights. Maintain data hygiene and a single source of truth for business metrics, translating raw data into clear recommendations.

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.

Develop and maintain interactive Tableau dashboards and reports that turn complex data into actionable business insights. Extract, transform, and analyze data from multiple sources using SQL, identify trends, troubleshoot data issues, and support data visualization best practices. Collaborate with business stakeholders to translate analytical needs into clear visual solutions and recommendations for nontechnical audiences.

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.

Gather, clean, and analyze data from multiple sources; build and maintain Power BI and Excel dashboards; run SQL queries and Python scripts for automation; collaborate with cross-functional teams to interpret trends and communicate insights; create documentation and improve reporting processes.

Perform exploratory analysis, build dashboards and reports (Tableau), write SQL queries, use Python for data cleaning and predictive models, collaborate with stakeholders, communicate insights, and maintain data models, pipelines, and quality checks.

Extracts, analyzes, validates, and abstracts clinical data from EHR/EMR systems for registries, reporting, and quality improvement programs. Reviews pathology, radiology, and treatment reports; maintains high accuracy and inter-rater reliability; protects patient confidentiality under HIPAA; prepares reports; and supports quality assurance activities. Requires advanced medical terminology knowledge, clinical data expertise, attention to detail, and independent work capabilities.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

Early-career Data Analyst who designs and owns core analytics, dashboards, and data pipelines. Analyze transaction, customer, and credit data to inform credit, fraud, AML, portfolio performance, unit economics, and growth. Build automations and workflows with SQL and Python, partner with cross-functional teams, and own compliance reporting and durable analytical systems.

Extracts, analyzes, validates, and documents clinical data from EHR/EMR systems for registries, quality reporting, and improvement programs. Reviews pathology, radiology, and treatment reports; maintains high accuracy and inter-rater reliability; protects patient confidentiality under HIPAA; supports quality assurance; and presents summarized findings. Requires advanced medical terminology knowledge, Excel proficiency, and independent analytical work.

Design, build, and govern HSW data solutions and analytics; deploy AI and automation into HSW processes; produce Power BI dashboards and regular reports; support Cority operations; drive data strategy, governance, and actionable insights to improve safety and operations.

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.

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.

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.

Partner with founders and cross-functional teams to analyze financial and operational data, build executive dashboards, create P&L and margin analyses, forecast and model unit economics, identify cost leaks, reconcile transactions, and present recommendations to improve profitability, cash flow, and business performance.

Design and scale transportation analytics and tooling to optimize network performance and reduce shipping costs. Build dashboards, routing/ship-speed optimizers, chargeback/dispute systems, and cost benchmarking engines. Deliver predictive and real-time KPIs, automate processes, improve data accuracy, and provide fast ad-hoc decision support for cross-functional stakeholders.