Top SQL Jobs in Pune

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.

Develop, maintain, and support the enterprise MDM platform across customer, supplier, contact, and item domains. Implement MDM features, data integrations, and complex SQL processing. Write and test code, perform SIT/UAT, triage incidents, resolve defects, support migrations, ensure data integrity, adhere to SDLC/CI-CD and change management, and maintain documentation while collaborating with business users, vendors, and cross-functional teams.

Develop, maintain, and support the enterprise MDM platform across customer, supplier, contact, and item domains. Implement MDM features, data integration/ETL, and complex SQL queries; write tests and participate in SIT/UAT. Triage incidents, perform root cause analysis, support migrations and onboarding, follow SDLC/CI-CD and change management, ensure security and SOX compliance, and collaborate with business, vendors, and offshore teams.

Develop, maintain, and support enterprise MDM platform across multiple domains. Implement features, data integrations, and complex SQL processing; write tests; troubleshoot incidents; support migrations; follow SDLC/CI-CD and compliance processes; collaborate with business, vendors, and cross-functional teams.

Develop, maintain, and support enterprise MDM platform across customer, supplier, contact, and item domains. Implement features, data integration/ETL, and complex SQL queries; write/tests code, resolve incidents within SLAs, support migrations and onboarding, ensure data quality/integrity, follow SDLC/CI-CD and compliance (SOX), and collaborate with business, vendors, and cross-functional teams.

Develop, maintain, and support the enterprise MDM platform across customer, supplier, contact, and item domains. Implement new MDM features, build data integration/ETL solutions, write and optimize complex SQL, produce high-quality code and tests, triage incidents to meet SLAs, support data migrations and profiling, and follow SDLC/Agile processes, security, and SOX compliance while documenting changes.

Lead development of production-grade generative AI systems: design and deploy LLM-based, multimodal, and agentic applications; build retrieval and KG-augmented pipelines; implement fine-tuning and alignment (LoRA/QLoRA, RLHF/RLAIF); deploy scalable APIs and MLOps; collaborate cross-functionally and mentor junior engineers.

Lead design and build of generative AI, multimodal, and agentic systems. Develop and fine-tune transformer models, retrieval/knowledge-graph augmented systems, and production APIs. Deploy and monitor ML services in cloud, collaborate cross-functionally, mentor engineers, and ensure safety, evaluation, and scalable MLOps practices.

Design and own end-to-end data platform architecture, build ingestion and transformation pipelines, model multi-tenant datasets, optimize Postgres and ClickHouse performance/cost, implement orchestration and observability, define data quality and reconciliation standards, and mentor data/product engineers.

Lead design, build, and operation of AI-powered product features across backend, frontend, and AI systems. Make architecture decisions, drive production deployments, improve code quality and reliability, mentor engineers, and own features end-to-end.

Build and productionize AI features across frontend and backend: document review, entity extraction, quote comparison, embeddings and LLM integrations, prototype from customer feedback, and create scalable reusable systems for insurance workflows.

Build AI-powered product features across backend, data pipelines, and UI. Implement RAG, embeddings, vector search, prompt design, and tooling to convert messy insurance documents into reliable, source-cited capabilities and collaborate with product and customer teams.

Design and build batch and real-time data ingestion pipelines, ETL/ELT solutions, data lakes and warehouses. Develop and optimize data models and microservices using Spring Boot. Ensure data quality, governance, security, observability, CI/CD, and cloud-native deployment on Azure/AKS. Collaborate across teams and support operational monitoring and performance optimization.

Design, develop, and maintain backend applications and microservices using C# and .NET Core. Build RESTful APIs, implement SOLID design patterns, write unit tests, work with Entity Framework and SQL databases, participate in code reviews, debugging, performance tuning, and Agile/Scrum team activities while collaborating with frontend, QA, and product teams.

The Lead Auto QA Engineer will develop test scripts, analyze regression failures, debug script issues, and enhance regression coverage within the financial services sector.

Build and own Firework's go-to-market systems and data infrastructure to generate enterprise leads end-to-end. Design CRM architecture, enrichment, scoring, routing, and automated outbound/inbound flows. Partner with Sales to define qualified leads, use AI tooling to prototype lead-gen automations, and continuously test and iterate to grow a qualified pipeline.

Build and maintain Supabase Lite: implement TypeScript-native backend compatible with PostgREST/Auth and @supabase/supabase-js, extend SQLite support, own CLI/tooling and upgrade paths, ensure compatibility with hosted Supabase, engage partners and open-source community.

Transform raw data into actionable insights by collaborating with business units, optimizing SQL queries, enhancing Tableau dashboards, and driving process improvements.

Assist in managing portfolio investment models, prepare investor reports, monitor performance, and resolve data discrepancies. Collaborate with senior team members for operational metrics and investor communication.

As a Senior Software Engineer at Summation, you'll design, develop, and scale software solutions for business planning and analytics, focusing on performance and customer impact.

The Senior QA Engineer will develop test plans, handle automated and performance testing, manage defects, and collaborate with teams for project progress.

The Data Operations Analyst develops custom product attribution based on client needs, utilizing tagging and machine learning; ensuring data mapping accuracy and project delivery.

As a Data QA Associate, you'll manage data cleaning and quality assurance processes, transforming receipt data into business insights, collaborating with remote teams, and ensuring data consistency and quality.

The Business Analyst will understand SaaS business models, onboard customers, manage data pipelines, and analyze customer KPIs using SQL.

Lead design and delivery of enterprise RPA and intelligent automation solutions. Own architecture, tool selection (UiPath, Power Automate, Blue Prism), integrations with ERPs and cloud, non-functional requirements, orchestration, CI/CD, and governance. Mentor developers and collaborate with stakeholders through discovery to production.