Top Tech Jobs & Startup Jobs in Mumbai

Build and maintain Databricks-based data integration and ETL pipelines using Python, PySpark, DLT, Delta Lake, and Unity Catalog. Design governed semantic models and self-service analytics layers, support data governance and access controls, and deliver executive dashboards in Tableau or Sigma. Partner with business stakeholders to translate requirements into actionable insights while maintaining production-quality code, documentation, lineage, and compliance in a regulated environment.

Manage global tax withholding and information reporting for securities services clients. Serve as a subject matter expert on FATCA, CRS, and U.S. tax Chapters 3, 4, and 61. Oversee data sourcing, validation, reconciliations, controls, issue management, and tax filings, including Forms 1042-S, 1042, and 1099. Partner with stakeholders, prioritize deliverables, escalate risks, and use automation, analytics, Alteryx, and Python to improve accuracy, efficiency, and audit readiness.

Build and manage large-scale data applications and data lake solutions for Finance and Securities Services. Integrate and model complex datasets, conduct analysis with SQL and Python, automate processes, and develop scalable analytics products. Manage projects end to end, including requirements gathering, BRDs, stakeholder coordination, and delivery oversight. Collaborate across Finance, Product, Operations, Technology, and developers, while leading AI/ML initiatives and establishing analytics best practices.

Lead design, build, deployment, and support of IBM Planning Analytics/TM1 solutions on AWS. Architect TM1 models, develop PAW/PAfE artifacts, manage TI processes and integrations, establish governance and SDLC controls, lead a TM1 team, drive AI-assisted engineering adoption, and partner with business stakeholders to optimize planning processes and ensure compliance and resiliency.

Build production-grade backend services, APIs, and AI-enabled workflows using Java or Python. Integrate LLMs, RAG, vector search, embeddings, and guardrails into enterprise applications. Develop React interfaces, database persistence layers, event-driven systems, CI/CD pipelines, testing strategies, and observability capabilities. Collaborate with business, operations, risk, and technology stakeholders to translate requirements into scalable, reliable, auditable solutions.

Leads credit risk governance for Wealth Management by maintaining policies, controls, procedures, committee governance, and issue remediation. Coordinates regulatory examinations, audits, and independent reviews; evaluates controls; identifies emerging and material credit risks; documents accountability across business, risk, and audit functions; and provides independent challenge and recommendations. The role also drives governance initiatives, reporting improvements, risk assessments, and special projects while partnering with stakeholders across the firm.

Supports end-to-end eDiscovery for litigation, regulatory inquiries, and investigations. Responsibilities include custodian and data-source identification, preservation, collection, review coordination, production, chain-of-custody documentation, vendor and stakeholder management, budgeting, milestone tracking, reporting, and process improvement. Advises legal teams, coordinates internal IT and external providers, manages sensitive data and competing priorities, and drives operational enhancements across global discovery processes.

Own the vision, roadmap, backlog, governance, and delivery of an enterprise Account and SSI golden-source platform. Translate operational, regulatory, risk, and data-quality requirements into prioritized user stories and controls. Lead agile execution, data stewardship, lineage, auditability, API and event-driven integrations, and downstream publishing. Partner with Compliance, Risk, Technology, Operations, and business leaders on KYC, AML, sanctions, settlement, reporting, remediation, and executive-level performance metrics.

Develops and maintains secure, scalable software solutions using Java, Kafka, cloud services, and modern engineering practices. Responsibilities include system design, coding, testing, troubleshooting, architecture documentation, data analysis, and operational stability. The role also requires responsible use of AI-assisted development tools, secure coding, CI/CD, resiliency, and collaboration within an agile engineering team.

Lead design and scaling of an agentic AI platform to automate the Data Development Lifecycle. Run discovery with business teams, translate needs into technical requirements, validate agent behavior and outputs, define success metrics, coordinate delivery, and drive adoption across lines of business while ensuring governance, controls, and executive communication.