Top Tech Jobs & Startup Jobs in Mumbai

Lead the decommissioning and migration of a legacy enterprise reporting platform to modern cloud analytics tools. Own report inventory analysis, rationalization, migration wave planning, requirements, tool evaluations, data-flow mapping, stakeholder alignment, governance, risk management, executive communications, user acceptance testing, change management, training, adoption, and cutover support across global financial-services teams.

Support global IT Project Services procurement operations across the full source-to-pay lifecycle. Manage Vendor Management Solution (VMS) platforms, vendor relationships and performance, stakeholder collaboration, compliance to contracts and strategic programs, reporting and analysis, process improvements, and SharePoint/documentation management to optimize contingent labor and sourcing practices.

Defines and manages Markets Sales data products, including product attributes, architecture, quality, accessibility, integrations, and tooling. Partners with Quant Research, Technology, Sales users, and analytics teams to translate requirements into development tasks, prioritize features, manage releases, resolve data quality issues, promote product reuse, and support effective data consumption across the firm.

Perform price verification, benchmark processes, fair value adjustment calculations, valuation controls, management reporting, and regulatory work. Partner with business, risk, finance, and functional teams to resolve valuation issues and ensure fair value. Enhance independent pricing and control frameworks, assess coverage gaps, implement efficiency tools, and support valuation-related initiatives involving complex financial products and derivatives.

Develop and support full-stack, data-enabled applications using Python, FastAPI, React.js, Databricks, SQLite, and SharePoint. Responsibilities include building REST APIs and user interfaces, creating production data workflows, implementing persistence, writing tests, supporting deployments and observability, troubleshooting operational issues, collaborating with stakeholders, and maintaining technical documentation. The role requires strong software engineering fundamentals, secure coding practices, communication, and ownership of iterative delivery.

Lead the design, development, and evolution of a centralized Snowflake data platform integrating data from 30–40 upstream systems. Build scalable pipelines, ETL/ELT processes, data models, quality controls, monitoring, and analytics-ready data products. Partner with engineering, product, data, reporting, and controls teams to resolve data issues, improve platform performance and resilience, and support AI/ML use cases. Provide technical leadership and mentorship while promoting strong coding, testing, documentation, and agile delivery practices.

Sources and pipelines qualified candidates globally across APAC, EMEA, and/or NAMR using recruiting platforms, social media, LinkedIn, and professional networks. Partners with recruiters and hiring managers, supports diverse talent sourcing, provides regional market intelligence, manages candidate engagement, discusses compensation expectations, and tracks sourcing metrics. Improves sourcing processes and advises recruiting teams on sourcing techniques, systems, controls, and policies while supporting stakeholders across time zones.

Measure, monitor and communicate credit and market risk across marketable-securities-backed lending, capital markets, and derivatives. Build analytics, stress testing and collateral frameworks; translate market events into actionable risk insights and recommendations. Collaborate with risk, lending, trading, finance and stakeholders to support governance, reporting and controls.

Lead product-area financial planning, forecasting, variance analysis, and executive reporting. Build dashboards, automate reporting, reconcile accounting data, produce business cases, improve controls and data quality, and support ad-hoc and special projects for senior stakeholders.

Implement and maintain reliable production systems: design and deliver small-to-medium projects, write maintainable code, triage and resolve incidents, reduce operational toil via automation, and improve observability and SLO/SLA monitoring while responsibly using enterprise AI capabilities.