Top SQL Jobs in Pune

Extracts, transforms, and analyzes media measurement data to identify insights, test hypotheses, and answer client and stakeholder questions. Leads data investigations, develops analytical solutions, supports sales feasibility reviews, and contributes to reporting tools and automation. Collaborates across teams, formulates technical approaches to open-ended problems, and improves analytical workflows using SQL, Python or R, ETL tools, cloud technologies, and Excel.

Build and maintain secure, scalable data pipelines, warehouses, and lakes. Design distributed processing architectures using AWS and Hadoop technologies, develop ETL and analytical solutions, and collaborate with data scientists on machine learning deployment. The role also involves technical design, advanced SQL and programming, stakeholder partnership, risk management, and potentially leading and developing a team.

Build, deploy, and maintain enterprise-grade backend software while partnering with the CTO and founding team. Own technical decisions, production reliability, scalability, security, and lifecycle improvements. Troubleshoot complex issues, develop prototypes and technical content, adopt emerging technologies, and collaborate with engineering, design, sales, and other stakeholders. The role requires strong backend, cloud, infrastructure-as-code, distributed systems, API, database, and generative AI experience, with independent execution in an in-person startup environment.

Own and develop mission-critical backend systems, cloud infrastructure, and LLM-powered production systems. Design scalable services using Python, REST, gRPC, Kubernetes, and Terraform; manage relational, NoSQL, graph, and vector data architectures; improve reliability, performance, and operational excellence; and provide hands-on technical leadership across backend, frontend, infrastructure, and AI systems.

Leads enterprise data management, modernization, governance, and AI transformation initiatives. The role architects scalable cloud data platforms and AI-ready data products, including GenAI and agentic AI solutions using LLMs, RAG, vector databases, knowledge graphs, and semantic layers. Responsibilities include executive client engagement, consulting, solution architecture, program and team leadership, delivery governance, financial performance, pre-sales, account growth, and mentoring senior data and AI professionals.

Leads enterprise Data and AI consulting, solution architecture, presales, and delivery. Designs data management, cloud modernization, governance, analytics, GenAI, and agentic AI solutions using modern data and semantic technologies. Develops proposals, RFP/RFI responses, SOWs, estimates, roadmaps, business cases, and reusable accelerators. Conducts executive client workshops, guides implementation teams, and ensures scalable solutions deliver measurable business value and ROI.

Senior Data Engineer responsible for migrating a production SaaS ETL and streaming platform to a Snowflake Native Application. The role includes redesigning ingestion, translating legacy transformations, implementing cross-account multi-tenant isolation, rebuilding core data models, addressing security and technical debt, validating production-scale patterns, and documenting migration decisions. Candidates need strong Snowflake, production ETL migration, streaming, cloud services, security, and multi-tenant SaaS experience.

Build, operate, and scale enterprise web applications using Python and React.js. Develop REST and GraphQL APIs, asynchronous processing, responsive interfaces, database queries, automated tests, and CI/CD workflows. Own features end to end, improve architecture and observability, modernize legacy systems, resolve outages, reduce technical debt, and mentor engineers. Collaborate with Product and Design in a remote, pod-based organization while leveraging AI coding agents.

Provide advanced technical support for enterprise database customers by diagnosing complex issues involving database internals, SQL performance, Linux systems, networking, and distributed applications. Reproduce bugs, perform QA, submit engineering reports, collaborate with development and infrastructure teams, improve support processes, and create documentation. The role includes scheduled IST hours and participation in an on-call rotation.

Build and maintain FinOps data pipelines, BigQuery and dbt models, cost attribution systems, forecasting and anomaly detection models, and cost-versus-revenue analytics. Identify and implement AWS and GCP savings opportunities, automate governance with Python, Terraform, and Lambda, and partner with Engineering, Finance, Product, and leadership on cloud costs, forecasting, reporting, and architecture decisions.

Design, build and maintain secure, scalable AWS data pipelines, data lakes and Snowflake-based warehouses. Develop ETL/ELT (DBT, PySpark), orchestration (Airflow), advanced SQL/PLSQL, and collaborate with data science to deploy ML models while leading teams and ensuring governance, controls and stakeholder alignment.

Owns end-to-end QA for the Shop & Scan platform, including test strategy, functional and regression testing, automation framework development, API and web/mobile validation, defect management, release readiness, and quality improvement. The role also promotes AI-assisted testing, collaborates closely with Agile stakeholders, and drives scalable automation and coverage improvements.

Build data infrastructure and reliable pipelines, analyze product usage, train traditional and LLM-based models, define product metrics, run experiments, and translate findings into product and go-to-market decisions. The role combines data science, data engineering, product analytics, machine learning, and stakeholder communication, with ownership across data modeling, evaluation, experimentation, and product insight generation.

Lead development of foundational platform services, including identity, authorization, search, and API infrastructure. Design scalable architectures, optimize database performance, build internal developer tools, improve observability and frontend reliability, and collaborate with product teams. The role includes writing tested code, conducting reviews, documenting platform capabilities, supporting internal users, and evaluating or integrating AI-assisted development and LLM-powered systems.

Designs and optimizes fulfillment solutions, facility layouts, process flows, labor models, automation strategies, pricing models, and cost structures. Conducts scenario modeling and supply chain financial analysis while partnering with sales, finance, operations, implementation teams, and prospective customers. Supports scalable, cost-effective solutions for fulfillment and warehousing operations.

Designs and maintains automated test frameworks and suites for functional, integration, load, performance, API, UI, and system testing. Develops test strategies, improves CI/CD automation infrastructure, validates distributed systems, identifies coverage gaps, investigates defects, and enhances software reliability and quality engineering practices in collaboration with engineering and release teams.

Build and maintain full-stack features for secure, high-volume fintech and cryptocurrency transactions. Develop Golang and Java backend services, Node.js and TypeScript APIs, and React/Next.js applications. Integrate third-party systems, implement OAuth 2.0 authentication, work with microservices, and ensure security, performance, reliability, and observability. Contribute to architecture discussions, code reviews, technical documentation, and end-to-end feature ownership in a fully remote environment.

The Senior Sales Engineer will provide technical leadership throughout enterprise sales cycles, translating customer business needs into storage and data-management solutions. Responsibilities include partnering with account teams and channel partners, conducting evaluations and benchmarks, configuring systems, delivering architecture presentations, responding to RFPs and RFIs, supporting interoperability testing, positioning solutions against competitors, and contributing to technical marketing. The role requires deep expertise in enterprise storage, distributed architectures, Linux, NFS, networking, cloud-native technologies, and customer-facing pre-sales engagements.

Supports FP&A across expense allocation, management reporting, budgeting, forecasting, variance analysis, revenue and cost analysis, and financial modeling. Maintains weekly, monthly, and quarterly reporting streams; prepares stakeholder materials; reconciles large datasets; and improves automated reporting processes using Excel and AI tools. Partners with Controllers, Finance Engineering, and business teams across time zones in a fast-paced financial services environment.

Develop and maintain Java Spring Boot microservices, REST APIs, and backend services for enterprise order management and supply chain applications. Design scalable, reliable, secure, and configurable product capabilities; troubleshoot production issues; write tested code; participate in reviews; and collaborate with product, QA, DevOps, and engineering teams. Use AI-assisted development tools responsibly for coding, debugging, testing, documentation, and productivity.

Designs and maintains scalable data pipelines and ETL/ELT workflows using Python, SQL, and Azure Databricks. Manages large structured and semi-structured datasets, data models, monitoring, quality controls, troubleshooting, and production support. Integrates LLM and Generative AI capabilities, including APIs, embeddings, prompt engineering, and RAG workflows, into data solutions. Collaborates with engineering, analytics, and business teams while following security, CI/CD, documentation, and maintainability best practices.

Develops, validates, deploys, and maintains SAS-based clinical data programming, dashboards, reports, and analytics solutions. The role supports clinical data review, reconciliation, risk-based quality management, centralized monitoring, site performance oversight, and study decision-making. Responsibilities include requirements gathering, data extraction and transformation, quality control, stakeholder presentations, documentation, SOP compliance, workflow automation, and mentoring less-experienced colleagues.

Design, develop, deploy, and maintain scalable distributed systems, real-time platforms, data pipelines, and analytics tools. Build data extraction, transformation, and loading systems using SQL and big data technologies. Work across low-level systems and distributed architectures, collaborate with data science and product teams, and mentor junior engineers.

Own end-to-end credit strategy for an Android lending workstream: set roadmap, forecasts, and P&L; design experiments and PD/eligibility rules; implement decision-engine rules; define back-testing, validation and rollout plans; monitor performance and drive corrective actions; collaborate cross-functionally and mentor other analysts to ensure controlled, profitable growth.

Build and operate enterprise integrations across Salesforce, CPQ, contract management, NetSuite, Workato, and cloud data warehouses. Develop event-driven billing automation, MCP servers for internal AI agents, governed APIs, monitoring, security controls, and audit-ready integration processes. Own reliability, incident response, documentation, and on-call coverage while supporting the Lead-to-Cash transformation and other company-wide systems programs.