Top Data Analyst Jobs in Mumbai

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

Supports liquidity regulatory reporting controls by documenting data flows, business data elements, lineage, transformations, and controls from booking systems to reporting platforms. Performs SQL-based data analysis, test-case development, functional and business testing, quality remediation, root-cause analysis, requirements management, stakeholder coordination, and management reporting. Contributes to implementation activities, change control, documentation standards, and training junior team members.

Analyzes large datasets to identify call center performance trends, quality assurance insights, operational issues, and customer experience improvements. Develops Power BI dashboards, performs root-cause and descriptive analytics, and translates findings into clear narratives for clients and nontechnical stakeholders. Collaborates with data scientists and consultants to align analytical outputs with business objectives.

Internship data analyst supporting dashboard monitoring, user behavior and content ecosystem analysis, A/B test evaluation, campaign performance analysis, data quality assurance, and metric documentation. The role uses SQL and Excel to derive insights on engagement, retention, conversion, and creator ecosystems, while collaborating with product and operations teams in a blockchain and digital assets environment.

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.

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.

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.

The Data Analyst maintains accurate data across CRMs and spreadsheets, builds reports and dashboards, investigates discrepancies, and develops scalable data models and database schemas. The role creates and monitors ETL pipelines using SQL, Python, and orchestration tools; integrates systems through APIs and webhooks; performs advanced data analysis; and translates business requirements into automated solutions. The position requires cross-functional collaboration, strong data governance, and reliable reporting.

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.

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

Design, build, and maintain Power BI dashboards and reusable tabular data models; administer Power BI Service; ingest and transform data using SQL/Python and ETL tools; support stakeholders with ad-hoc reporting, documentation, demos, and Power Platform requests.

Leads data foundations initiatives by translating business requirements into scalable data solutions, pipelines, models, governance standards, and technical specifications. Partners with engineers, architects, and global stakeholders to improve data quality, reliability, observability, metadata, and lineage using GCP, Monte Carlo, and Collibra. Serves as a technical subject matter expert, mentors analysts, communicates delivery progress, and supports automation, AI enablement, compliance, sustainability, and real-time analytics.

Lead governance for enterprise unstructured data, including documents, emails, media, PDFs, and chat logs. Develop data policies, ownership models, security and access standards, retention, lineage, quality monitoring, audit methods, and remediation processes. Inventory and classify content, configure governance software, integrate assets into enterprise catalogs, and collaborate with data owners, cybersecurity, Office 365, and governance teams to ensure compliance and responsible data use.

Leads Supply Chain data foundations by translating business needs into technical specifications, designing scalable data pipelines on Google Cloud Platform, and improving data quality, governance, metadata, lineage, security, and reliability. Partners with business and technology stakeholders, mentors analysts, maintains data models and integrations, and supports sustainability reporting, digital twins, predictive analytics, regulatory compliance, automation, and AI enablement.

Designs and maintains ETL pipelines integrating banking-system data into analytics platforms; builds data models for reporting, analytics, and machine learning. Collaborates with analysts, data scientists, and stakeholders to define requirements and delivers insights across risk, credit, and liabilities. Ensures data quality, security, governance, and compliance while monitoring and troubleshooting workflows and infrastructure performance.

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.

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.

Manage and execute customer communication campaigns for consumer banking marketing and product teams. Responsibilities include campaign list creation, campaign design and build, QA, maker-checker controls, workflow execution, performance tracking, and use of enterprise marketing platforms such as HCL Unica. The role requires SQL-based customer analysis, collaboration with analytics and technical teams, prioritization of business-critical work, and timely, error-free campaign delivery.

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

The Data Analyst will support product marketing initiatives by analyzing data, tracking KPI progress, developing dashboards, and providing actionable insights to inform decision-making across business units.

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.

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.

Supports client operational and analytical processes by executing procedures, validating deliverables, identifying process improvements, coordinating stakeholders, testing updated workflows, documenting operational models, researching issues, and investigating client questions. Collaborates with senior analysts, delivery leads, engineering teams, and internal stakeholders to provide accurate, timely client results across multiple tasks and time zones.