Top SQL Jobs in Pune

Lead implementation and deployment of Amtech ERP solutions (cloud or on-prem), manage data migration and EDI integrations, provide technical training and go-live support, troubleshoot complex issues, mentor junior consultants, and contribute to sales and process-improvement initiatives while maintaining high billable utilization.

Own compensation operations for GTM teams: design scalable processes, administer plans, manage payouts, ensure governance and compliance, build reporting and field support, and partner cross-functionally with Legal, HR, Finance, and Sales.

Lead a global support and managed services team for an AI-powered materials science SaaS: own SLAs, triage escalations, drive incident resolution with Engineering, build reporting, coach and hire staff, and personally handle select high-priority technical tickets.

Administer and support Microsoft 365 productivity platforms, resolve escalated technical issues, design permanent solutions and automations, lead projects, deliver trainings, create reports, and collaborate across teams to improve service stability.

Assess business opportunities and promote data science adoption. Build, test, and operationalize ML and GenAI solutions; design ML/LLM pipelines (RAG, prompt engineering). Develop scalable cloud functions and microservices, integrate APIs with ApigeeX, monitor performance, and collaborate with stakeholders to drive solution adoption.

Design, develop, and maintain ETL/data pipelines using Microsoft Fabric and Azure. Build and optimize OneLake/Lakehouse solutions, integrate multiple data sources, implement transformations with SQL, Python, and PySpark, ensure data quality and performance, collaborate with stakeholders, and maintain documentation.

Design, build, and maintain data pipelines, warehouses and lakes; implement processing and analysis algorithms; ensure data security and quality; collaborate with data scientists to deploy ML models; lead teams or complex assignments and influence cross-functional stakeholders.

Design, develop, and deliver scalable Java full-stack solutions using Spring and Angular. Collaborate with product and design, follow secure coding and testing practices, implement CI/CD, and lead or mentor peers while ensuring alignment with business objectives and governance.

Design, develop, and optimize large-scale PySpark ETL/ELT pipelines on Databricks. Implement Delta Lake lakehouse architectures, tune Spark jobs, write complex SQL, monitor production, enable CI/CD, mentor junior engineers, and collaborate with stakeholders on scalable data solutions.

Design, implement, and maintain CIAM and access management solutions (authentication, authorization, RBAC, provisioning). Integrate CIAM with applications, enforce access policies, audit controls, troubleshoot systems, and mentor junior engineers while ensuring security best practices, compliance, and clear documentation.

Design, build, and deploy AI agents and machine learning models; integrate ML/NLP into full-stack applications; develop APIs and data pipelines; deploy and manage services on AWS; collaborate with frontend/backend teams and maintain CI/CD, databases, and production monitoring.

Design, develop, and maintain scalable Java backend applications and microservices. Build and consume RESTful APIs, deploy with Docker and Kubernetes on GCP, write and optimize SQL, and collaborate with cross-functional teams to troubleshoot and improve performance.

Design, build, and evaluate classical and Bayesian ML models; perform EDA, feature engineering, and data wrangling using Python and SQL; collaborate with engineers to source and validate pipelines; track and communicate model performance; recommend retraining strategies; and produce well-documented, production-ready code and notebooks.

The Senior Product Manager will lead product roadmaps, mentor teams, manage execution, collaborate with engineering, and monitor product performance across multiple regions.

Design and build scalable backend systems and AI-powered solutions (LLMs, RAG, retrieval, agents). Own projects end-to-end, optimize performance, drive AI engineering standards, mentor engineers, and integrate AI with enterprise systems.

Lead design and delivery of scalable Python backend and AI platforms. Architect microservices, integrate LLMs and vector retrieval, build AI workflows, optimize data pipelines with Databricks and SQL, lead cloud deployments on Azure/AWS, mentor engineering teams, and collaborate with product and data science to productionize Generative and Agentic AI solutions.

Design, build, and maintain high-performance backend systems and scalable APIs using Python and FastAPI. Integrate AI-driven solutions (Generative/Agentic AI), work with Databricks and SQL/RDBMS, collaborate with cross-functional teams, optimize performance, and contribute to architecture and technical decisions.

Early-career Data Analyst who designs and owns core analytics, dashboards, and data pipelines. Analyze transaction, customer, and credit data to inform credit, fraud, AML, portfolio performance, unit economics, and growth. Build automations and workflows with SQL and Python, partner with cross-functional teams, and own compliance reporting and durable analytical systems.

Design, build, test, and debug complex applications following SDLC and QMS standards. Estimate effort, resolve high-complexity issues, recommend process improvements, enforce schedules, mentor junior staff, and ensure regulatory/QMS procedure compliance.

Provide technical ownership for Oracle Cloud applications: support, maintenance, enhancements, integrations, vendor validation, and quarterly update testing. Collaborate with product owners, integration and infrastructure teams to design, build, document, and test solutions following best practices and continuous improvement principles.

Senior supply chain consultant to support presales, RFPs, requirements analysis, solution design, and delivery. Lead discovery workshops, fit-gap analysis, process mapping, and stakeholder management to define scalable, analytics- and AI-enabled planning and execution solutions across ERP and planning platforms.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

Implement Vena for customers: configure data models, financial templates and reports, integrate data, automate workflows, run workshops to gather requirements, enable adoption, and work with Project Managers to deliver projects on time and on budget.

Own and evolve the solution architecture for Acterys within a cloud SaaS platform. Design scalable, secure, high-performance data-rich systems; guide engineering delivery, perform design reviews, maintain architecture artifacts, enable teams, drive proofs-of-concept, and promote AI-assisted tooling and governance.

As a Backend Engineer at Trust Wallet, you'll develop backend features for multiple platforms, maintain infrastructure, ensure system monitoring, and foster team growth.