Top SQL Jobs in Pune

Develop and support full-stack applications using Java, Spring Boot, React, and TypeScript. Design REST APIs, microservices, secure authentication flows, database integrations, and cloud-native solutions. Build containerized applications with Docker and Kubernetes, implement automated testing and CI/CD pipelines, troubleshoot across application layers, and establish observability practices. The role also involves documenting architectural decisions, making engineering trade-offs, and mentoring junior engineers.

Develop and support full-stack applications using Java, Spring Boot, React, and TypeScript. Design REST APIs and microservices, integrate relational databases, secure applications with OAuth2/OIDC, and deploy containerized solutions on Kubernetes and Azure. Build automated tests, CI/CD pipelines, observability, and cloud-ready distributed systems. Troubleshoot across application layers, document architectural decisions, make engineering trade-offs, and mentor junior engineers.

Administers SAP and non-SAP Oracle database environments across production and non-production systems. Responsibilities include installation, configuration, performance tuning, capacity planning, backup and recovery, Data Guard, RAC, Exadata monitoring, patching, security remediation, disaster recovery, incident support, and collaboration with infrastructure teams and Oracle support. Provides 24/7 shift and on-call support, participates in change management, and contributes to database architecture and technical solutions.

Lead reliability-focused technical programs across Mastercard’s authentication platforms. Coordinate Agile ceremonies, resource planning, backlog prioritization, dependencies, release governance, platform upgrades, migrations, and production rollouts. Partner with Engineering and SRE teams to improve availability, resiliency, performance, scalability, operational readiness, observability, automation, and disaster recovery. Manage risks and stakeholder communication while influencing cross-functional teams and driving continuous operational improvement.

Manages software engineering teams and owns end-to-end delivery of analytics and business intelligence solutions. Responsibilities include people management, technical strategy, architecture and system design, code and deliverable reviews, quality and security oversight, technical debt management, innovation, stakeholder coordination, and Agile delivery. The role requires expertise in React.js, .NET, AWS, databases, Hadoop, Spark, Databricks, big-data analytics, CI/CD, DevOps, and automation.

Leads quality assurance and software testing for large-scale card payment authorization systems. Develops test strategies, plans, automation, regression assessments, and release validation; translates requirements into test methods; performs functional, system, UAT, and integration testing; manages defects and root-cause analysis; mentors team members; and collaborates with developers, business teams, and payment-domain experts.

Designs, builds, and operates production-grade agentic AI systems using Python, LLM orchestration, tool calling, retrieval, memory, multimodal models, and LLMOps. The role develops scalable backend services, observability, RAG and Graph-RAG systems, model evaluation, and responsible AI safeguards. It also mentors engineers, establishes GenAI engineering standards, and productionizes emerging AI capabilities across enterprise applications.

Build and operate production-grade agentic AI systems, including tool-calling layers, Python backend services, multi-agent orchestration, memory, retrieval, observability, LLMOps, and multimodal pipelines. Develop RAG and Graph-RAG systems, fine-tune and evaluate foundation models, implement responsible AI controls, and mentor engineers. The role requires strong backend engineering, API integration, cloud, distributed systems, and production LLM application experience.

Owns the semantic and context layers that enable AI agents to accurately interpret business questions and query enterprise data. Defines metrics, entities, business rules, synonyms, and retrieval-ready context; partners with AI, data, architecture, governance, and business teams; evaluates agent outputs using golden queries; and establishes documentation, quality assurance, versioning, and change-management processes.

Designs, builds, and operates production-grade agentic AI systems and generative AI applications. Responsibilities include tool-calling infrastructure, Python backend services, agent orchestration, memory and retrieval systems, observability, LLMOps/MLOps pipelines, multimodal AI, model adaptation, responsible AI, and production evaluation. The role also mentors engineers and establishes engineering standards for enterprise generative AI development.

Lead architecture and technical strategy for an enterprise generative AI platform supporting agentic systems, tool calling, multi-agent orchestration, memory, retrieval, inference, LLMOps, observability, security, and responsible AI. Define reusable standards, evaluate models and platforms, guide architecture decisions, collaborate with engineering, product, security, and data teams, mentor technical leaders, and build prototypes for high-scale, reliable production systems.

Develop secure, scalable full-stack applications using Java, Spring, REST APIs, relational databases, and modern frontend frameworks. Responsibilities include designing software, building responsive interfaces, participating in architecture and Agile ceremonies, supporting testing, and collaborating with product and technical teams. The role also involves cloud deployment, microservices, CI/CD, containerization, Databricks and big data workflows, and integrating AI/ML services and development tools.

Develop scalable, highly available Java enterprise applications and microservices for Mastercard’s Account Level Management platform. Responsibilities include low-level design support, effort estimation, unit and integration testing, peer reviews, mentoring, task reporting, process compliance, and knowledge sharing. The role involves cloud deployment, database and messaging technologies, Agile development, security practices, and collaboration with engineering teams to deliver quality software on schedule.

Provides architecture and technical delivery leadership for secure, scalable, highly available payment-network services. Defines cross-platform architecture, APIs, resiliency, security, observability, and operational standards; coordinates releases, dependencies, defect resolution, and multiple engineering workstreams. Leads architecture reviews, develops technical architecture documents, mentors engineers, establishes reusable engineering patterns, and drives multi-region resilience, disaster recovery, reliability engineering, and enterprise technology strategy across globally distributed teams.

Design, develop, test, deploy, and support secure, scalable payment-network software using Java, Spring Boot, microservices, REST APIs, Kafka, and event-driven architecture. Troubleshoot production and performance issues, contribute to CI/CD, observability, resiliency, and automation, and collaborate across engineering, product, architecture, and operations teams. Provide technical leadership, mentor team members, and drive decisions across workstreams.

Build, test, release, monitor, and support platform services, APIs, connectors, and automation for customer data exchange and pipeline orchestration. Deliver components independently, write tests and documentation, replace manual processes with code, investigate production issues, and contribute to design, estimation, code reviews, and root cause analysis. The role uses cloud technologies, data platforms, secure coding practices, and CI/CD.

Leads client-facing technology consulting engagements for manufacturing and industrial operations. Responsibilities include OT and industrial data strategy, solution architecture, SDLC delivery, Unified Namespace and data-layer design, client relationship management, account expansion, cross-functional team leadership, validation, change management, and ROI delivery. The role requires deep expertise in plant-floor systems, industrial connectivity, cloud, data engineering, and life-sciences or pharmaceutical manufacturing.

Develop and maintain scalable full-stack applications using Java, Spring Boot, React, REST, gRPC, microservices, databases, and event streaming. Design APIs, user interfaces, automated tests, and optimized database solutions while applying TDD, CI/CD, and AI-assisted engineering. Own initiatives through production, troubleshoot issues, participate in architecture and code reviews, mentor engineers, and promote secure, maintainable, high-performance development practices.

Develop and scale globally relevant data analytics and agentic AI products for enterprise and credit risk customers. Partner with analytics, machine learning, engineering, operations, legal, customer experience, commercial, and product teams. Gather customer feedback, analyze data, define product direction, create requirements and user stories, communicate product updates and risks, and support go-to-market initiatives throughout the product lifecycle.

Leads architecture and development of highly available, globally distributed payment systems operating at massive scale. Designs reusable libraries, platforms, service interactions, and enterprise architecture standards while driving scalability, resiliency, performance, security, and cost improvements. Guides technical strategy across products and programs, resolves complex distributed-systems challenges, influences engineering decisions, consults across teams, and communicates technical insights through presentations, publications, and thought leadership.

Leads AI-enabled analytics engineering and commercial analytics workstreams for life-sciences and other clients. Builds Databricks insight pipelines, agentic LLM workflows, conversational analytics, evaluation harnesses, governed data products, and production-quality software. Structures ambiguous business questions, applies advanced analytical methods, integrates complex data sources, and translates findings into decisions and client-ready deliverables. Manages and coaches teams of 2–4, oversees quality and delivery risks, supports client stakeholders, and contributes to proposals and capability development.

Build and maintain Databricks analytics pipelines, LLM agent tools, evaluation harnesses, data guardrails, and tests while delivering commercial analytics for client teams. Analyze varied healthcare, life sciences, CRM, financial, and operational datasets using segmentation, forecasting, cohorts, and test-and-control methods. Present insights clearly, manage modules end to end, guide Associates, support SIT/UAT, and collaborate directly with clients.

Leads the design, development, integration, testing, and delivery of cardholder services applications. Provides hands-on technical leadership across Java and Spring Boot services, React or Angular applications, APIs, databases, event-driven integrations, and cloud platforms. Drives architecture decisions, technical evaluations, scalability, security, resiliency, CI/CD, production support, and engineering best practices while mentoring engineers and collaborating across Product, Engineering, Architecture, and QE teams.

Develops, tests, maintains, and troubleshoots enterprise data pipelines and analytical data solutions using Alteryx, Microsoft SQL Server, and Microsoft Fabric. The role focuses on data integration, transformation, quality, security, documentation, monitoring, operational resiliency, and cloud-native engineering patterns. It also involves collaborating with technical and business stakeholders to translate requirements into reliable, maintainable data products.

Develop secure, scalable data pipelines and data engineering solutions using Spark, Scala, Python, Java, Hadoop, and object storage. Build and maintain data warehouse projects, automate data ingestion and movement workflows, enforce data standards, and support production incidents. The role requires strong SQL and database expertise, analytical debugging skills, collaboration across distributed teams, and continuous process improvement.