Top SQL Jobs in Pune

Own and drive the Clearing & Settlement product within an issuer processing platform: define roadmap, translate scheme requirements (Visa, Mastercard) into product features, manage clearing, settlement, reconciliation, reporting, exception handling and controls, write requirements and user stories, and coordinate delivery across Engineering, Operations, Finance, Compliance and Client Delivery.

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 and operate ingestion and transformation pipelines to turn messy insurance data into clean datasets. Design bronze/silver/fact layers, model and tune Postgres and analytical stores, define KPIs and reconciliation checks, orchestrate observable data jobs, and ensure end-to-end data quality for analytics and AI products.

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.

Lead Compliance Data Analytics to research and analyze risk patterns (fraud, account takeover, payment fraud), deploy and iterate rules/models, partner with stakeholders to balance user experience and risk mitigation, drive business-centric analytics and strategic metrics, and build and manage a high-performing compliance analytics team.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

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.

Build and deploy production-ready GenAI systems (LLM, RAG, agentic agents) and document intelligence pipelines. Work with LangChain/LangGraph/LlamaCloud, embeddings and vector DBs, deploy on AWS/GCP/Azure, and apply ML/MLOps and model evaluation. Deliver fast, independent end-to-end solutions as a freelance/consultant.

Build and maintain full-stack web applications using React/Vue frontends and Java/Spring Cloud microservices. Design and consume REST/AI model APIs, work with SQL and NoSQL databases, use AI-assisted development tools, own features end-to-end, collaborate across product and design, ensure high-quality UI/UX, write tests, and contribute to documentation and architecture.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Internship role to develop and deploy user-growth algorithms: user segmentation, recommendations, LTV/churn/conversion models, A/B testing, causal inference analyses, and collaborate with product and engineering to drive measurable growth.

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.

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.

Remote internship supporting recruiter data operations: clean and analyze data, maintain website hosting and data structures, build API calls and automation scripts, perform web scraping, and communicate findings to stakeholders.

Design, build, and scale cloud-native Python backend services and data-backed applications. Develop RESTful APIs, microservices, and asynchronous event-driven systems. Deploy and operate production workloads on Kubernetes and at least one public cloud (AWS or Azure). Work with cloud data warehouses (Snowflake or Databricks) and relational databases, ensuring scalable, reliable distributed systems.

Build and prepare data pipelines: mapping, cleansing, transformation, integration, and wrangling using Python and SQL. Perform feature engineering for structured and unstructured data and support API and web app deployment for data products.

Design, build, and maintain scalable ETL/ELT data pipelines on GCP/BigQuery using Python and Spark. Integrate systems (APIs, Oracle EBS), implement workflow orchestration, ensure data quality and security, monitor performance, and document processes while collaborating with analysts and business teams.

Design, operate, and secure scalable batch and streaming data pipelines and platforms. Own ingestion, transformation, serving, data quality, and access controls. Partner with product, risk, compliance, and InfoSec to ensure production reliability, correctness, and audit readiness for financial data.

Design, build, and optimize Snowflake data models and dbt pipelines. Create Power BI reports and paginated RDLs with DAX and row-level security. Manage CI/CD with Azure DevOps, version control with Git, enforce data quality and governance, and optimize warehouse cost and performance while collaborating with business stakeholders.

Design, develop, and maintain SAP BODS ETL jobs for data extraction, transformation, and loading. Collaborate with analysts and DBAs, implement data quality checks, optimize job performance, document data mappings and lineage, and support data modeling for BI and reporting.

Develop and maintain web applications using .NET, SQL, and APIs; implement responsive frontends with React (or Angular/Bootstrap); ensure performance and quality; participate in Agile/Scrum ceremonies; collaborate with cross-functional teams; follow version control and deliver solutions on schedule. Immediate joiner preferred.

Design, develop, test, and maintain high-performance, scalable Java/Java EE applications. Participate in full SDLC, produce efficient, testable code, assist releases, and support architectural reviews and continuous improvement.