Top Data Analyst Jobs in Mumbai

Maintain and transform investment data into actionable insights by building data systems and pipelines, performing complex analysis, visualizing results, improving data quality, and collaborating with clients and product teams.

As a Data Analyst, you'll analyze complex data sets using statistical techniques, collaborate with SMEs, and prepare reports for stakeholders.

Perform gap analyses across trading data from multiple source systems, identify discrepancies, build automated reports using Python and SQL, create visualizations (Power BI or Python libraries), present findings to stakeholders, and coordinate with upstream/downstream teams to implement logic and document requirements.

Lead SOX compliance and ICFR activities including internal controls design, risk assessment, audit coordination, governance reporting, operational effectiveness, and stakeholder communication.

Collect, extract, standardize, and validate Private Equity financial data from GP/LP documents and portals. Tag metadata, perform QC, resolve exceptions, run basic reporting and trend analysis, support data cleansing and automation (SQL), document processes, and collaborate to meet quality and timeliness targets across global shifts.

Design, maintain, and administer internal Power BI dashboards, datasets, and models for Finance and corporate functions. Perform data ingestion and transformation using SQL/Python, develop reusable tabular models, support ad-hoc reporting and Power Platform requests, document assets, and deliver demos and training to stakeholders.

The Data Analyst - Senior Associate PMA will manage data, support program reporting, coordinate with teams, and create communication collateral. Responsibilities include data analysis, monitoring, and engaging with stakeholders.

Design, build, and operate Azure/Databricks lakehouse pipelines (batch and streaming) with governance, data quality, observability, and cost controls. Model curated datasets and semantic layers in Power BI, manage PostgreSQL replication/CDC to lakehouse/Synapse, enforce security/compliance, and collaborate with product owners and data stewards to certify enterprise datasets.

Design and operate an Azure + Databricks lakehouse; build batch and streaming ingestion pipelines with CDC, automated data quality, CI/CD and observability; model curated datasets and semantic layers for Power BI; enforce security/compliance controls and cost optimization; collaborate with product owners and data stewards.

Clean, prepare, and analyze corporate disclosure data (primarily in Excel); draft research reports and briefings; monitor market and ESG/AI developments; refine surveys and review company feedback; support engagement with companies and investors; respond to internal data queries; collaborate with analysts and team leads. Role requires office attendance three days a week and working 11:00–20:00 IST.

The Data Analyst will analyze data, develop dashboards, conduct statistical analyses, and collaborate with teams to provide insights that drive business decisions.

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

Lead analytics for Organic Search, Paid Media, and Direct-to-Site channels. Own reporting, build automated dashboards, run advanced SQL and Python analyses across Oracle and BigQuery, integrate Adobe Analytics and SEO tools, and deliver actionable cross-channel insights to improve acquisition, content, and media efficiency.

No Data Analyst responsibilities are described. The posting instructs candidates to register on the JobDials portal, post their CV, and follow the company on social media. This is a recruitment/registration notice rather than a role description.

Serve as the gatekeeper for regulatory data: perform upstream change impact analysis, triage data incidents, trace lineage with complex SQL, define test plans and JIRA requirements, and coordinate between reporting and technology teams to prevent report regressions.

The role involves data analytics with a focus on querying large data sets, visualization using Tableau, and applying quantitative skills, predominantly in the FMCG and Food & Distribution sectors.

The Data Analyst prepares, analyzes, and validates data, applying statistical methods and visualization techniques to derive insights and support business objectives. Communicates findings effectively and collaborates with Data Engineers for model and dashboard implementation.

The Data Analyst will analyze data to provide insights for decision-making across pricing, go-to-market strategy, and revenue performance, collaborating with stakeholders.

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.

Design, build, and maintain cross-vendor market data pipelines and QA processes. Investigate complex data issues, handle escalations, collaborate with product and engineering via JIRA, and ensure data accuracy for equities fundamentals, estimates, and market data.

The Senior Business Analyst will analyze and resolve data quality issues, coordinate with data teams, document business requirements, and implement data governance frameworks to improve business productivity and data management processes.

Perform advanced data analysis and statistical modeling in R, build and optimize complex SQL queries, ensure data accuracy and quality, collaborate with stakeholders to deliver insights, and optionally process large datasets using Hadoop or similar big-data technologies.

Combine customer marketing and data analysis to drive engagement and retention. Collect and clean data from CRM, web, and campaign tools; build dashboards and segments; run email, loyalty and upsell campaigns; measure ROI and retention; design sales incentive schemes; support forecasting, territory planning, and sales-marketing alignment.

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.

Perform full-stack on-chain and product analytics: query on-chain data, profile ecosystem actors, benchmark protocols, define KPIs, build dashboards, and translate findings into actionable briefs for strategy, BD, product, and growth teams.