Top SQL Jobs in Pune

Develop and support secure, scalable full-stack Java applications using Spring, REST APIs, databases, and React or Angular. Collaborate with product owners, participate in architecture and Agile planning, create usable interfaces, support system and user acceptance testing, and contribute to CI/CD automation and software releases.

Build and enhance Ethoca products across the full software development lifecycle, including design, development, testing, deployment, configuration, and documentation. Develop scalable test automation frameworks, review quality solutions, promote shift-left practices, and contribute to architecture and design decisions. Collaborate with product and engineering teams, manage risks, integrate services, mentor engineers, and improve operational metrics. Work with microservices, distributed systems, cloud-native applications, APIs, CI/CD platforms, and data validation.

Design, build, and deploy AI and Generative AI solutions using LLMs, agent frameworks, and RAG. Develop scalable AI/ML pipelines, cloud-native integrations (Azure/Databricks/AWS), and MLOps/LLMOps deployments. Integrate AI with APIs, databases, and internal apps. Implement Responsible AI practices (bias detection, hallucination mitigation, explainability, safety guardrails). Monitor, test, and maintain production AI systems while staying current on Generative AI trends.

Leads MetLife’s India-based enterprise data engineering organization, overseeing data architects, engineers, platform engineers, and scrum leads. Responsibilities include setting data engineering roadmaps, designing scalable data architectures and platforms, directing ETL/ELT solutions, improving data governance and storage, and delivering trusted data products. The role also owns talent acquisition, team development, cultural transformation, stakeholder alignment, and strategic data-driven innovation across global financial services operations.

Build and maintain data validation rules, test cases, quality artifacts, profiling processes, anomaly detection, and quality reports. Perform data quality checks across testing lifecycle stages and collaborate with business, technology, operations, governance, architecture, engineering, and analytics teams. Lead solution design and estimations, work across cloud and on-premises data environments, and mentor Data Quality Analysts.

Lead the strategy, architecture, and evolution of enterprise data platforms supporting secure data exchange, discovery, governance, integration, and self-service consumption. Establish scalable patterns for data quality, lineage, observability, privacy, and security while reducing bespoke workflows through automation. Provide technical leadership across engineering organizations, influence architecture decisions, mentor technical teams, and translate complex business needs into reusable cloud and on-premises data solutions.

Design and develop a scalable automated locates platform for securities finance using Java, Spring, microservices, distributed systems, containers, AWS, SQL, caching, and messaging technologies. Build high-performance enterprise applications, optimize transactional data models and queries, integrate real-time processing systems, and collaborate with development, business analysis, QA, and operations teams.

Leads global workforce analytics and reporting, translating HR data into actionable insights for business leaders. Responsibilities include dashboard development, headcount reporting, forecasting, data quality management, governance, dimensional data modeling, advanced SQL analysis, and collaboration with HR systems, engineering, and FP&A teams. The role also explores Generative AI to automate reporting and enhance employee analytics.

Provides technical and delivery leadership for large-scale payment-network initiatives. Defines secure, scalable, highly available architectures; coordinates releases, dependencies, defect resolution, and cross-team engineering execution; leads design reviews and architecture governance; establishes standards, guardrails, reusable patterns, and resiliency strategies; and mentors engineers and technical leads. The role emphasizes distributed systems, multi-region recovery, observability, reliability engineering, security, operational readiness, and stakeholder communication across globally distributed teams.

Design, build, and maintain scalable data pipelines and cloud data platforms to support AI/ML workloads. Deploy, monitor, and operationalize machine learning models, implement CI/CD and MLOps, ensure data quality, scalability, and governance while collaborating with data scientists, engineers, and stakeholders.

Collaborates with internal and client teams to analyze business problems, translate requirements into technical designs, and implement technology solutions. Develops technical features using appropriate methodologies, testing practices, and technology stacks. Supports project implementation planning, interprets business requirements, and contributes to small- and medium-scale client engagements involving databases, programming, cloud platforms, and analytics.

Develops and maintains data engineering solutions involving ingestion, aggregation, processing, curation, modeling, and analysis of high-volume data. Uses Cloudera, Databricks, AWS, Python, PySpark, SQL, and related tools to unify data assets, generate insights, support business intelligence, and enable fraud, security, and digital identity products. Partners with product, data science, platform, technology, client, and sales teams to deliver data solutions, prototypes, and enhancements.

Designs, develops, and maintains Java-based test automation frameworks for payment processing platforms. Builds functional, API, integration, regression, UI, and end-to-end test suites covering authorization, clearing, tokenization, and payment workflows. Integrates automated tests into CI/CD pipelines, manages test data and environments, analyzes failures, and collaborates with engineering teams to improve software quality and automation efficiency.

Design, develop, test, deploy, and support secure, scalable Java and Spring Boot microservices, REST APIs, and Kafka-based event-driven integrations. 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 engineers, and drive decisions across workstreams while applying secure coding and software design practices.

Designs, develops, tests, and supports scalable Java payment-processing applications and automated validation frameworks. Builds solutions for authorization, tokenization, clearing, settlement, ISO 8583 messaging, transaction routing, and exception handling. Integrates testing into CI/CD pipelines, supports production systems, troubleshoots complex issues, participates in architecture and code reviews, and mentors engineers. Collaborates across distributed engineering, product, and operations teams while promoting automation and software quality practices.

Build data engineering solutions that ingest, aggregate, unify, and analyze high-volume data from diverse sources. Develop data pipelines and models using Cloudera, Databricks, AWS, Hadoop, Python, and SQL. Partner with product, data science, platform, technology, client, and sales teams to deliver actionable insights, prototypes, business intelligence, and innovative cyber, fraud, security, and digital identity products.

Designs, develops, tests, deploys, and supports secure, scalable payment-network software using Java, Spring Boot, Angular, Kafka, microservices, and cloud-native practices. Builds responsive front-end experiences, integrates secure APIs, applies secure and reusable design principles, troubleshoots production issues, contributes to CI/CD and observability, and collaborates across engineering and product teams. Provides technical leadership, mentors team members, and drives decisions across workstreams.

Develops, tests, validates, and supports large-scale batch and real-time data platforms using Spark, Kafka, and NiFi. Builds resilient data pipelines, validation frameworks, distributed storage solutions, deployment automation, and operational tooling. Optimizes performance, scalability, and reliability; supports production troubleshooting and incident resolution; contributes to architecture, CI/CD, documentation, code reviews, and engineering standards; and mentors junior engineers.

Lead design and build cloud-native batch and real-time data platforms. Develop scalable ETL/ELT and streaming pipelines (Spark, Kafka, Flink), ensure data quality, governance, observability, security, cost optimization, and drive platform engineering excellence and team mentorship.

Develop and maintain secure, high-quality software components for Mastercard’s unified UI platform. Responsibilities include coding, testing, deployment, troubleshooting, refactoring, automation, API integration, release pipeline orchestration, and architecture understanding. The engineer will contribute to Agile processes, conduct demos, improve operational metrics, promote engineering standards, review code, mentor team members, and collaborate with product owners to deliver reliable, accessible customer experiences.

Tests liquidity risk and regulatory reporting releases across PRA, EBA, HKMA, and US Federal Reserve requirements. Responsibilities include SQL-based data validation, test strategy and execution, defect management, UAT dashboards, requirements gathering, data-gap analysis, issue resolution, and stakeholder communication. The role also supports finance data quality initiatives, regulatory compliance, operating-model transitions, change implementation, and coordination across Finance, Risk, Business, and IT teams.

Build and manage Adobe Journey Optimizer, Adobe Campaign Classic, and Adobe Experience Platform solutions for personalized omnichannel customer journeys. Responsibilities include campaign workflows, JavaScript and SQL development, data ingestion and transformation, XDM schemas, identity stitching, audience activation, APIs, microservices, integrations, analytics tracking, testing, troubleshooting, documentation, and privacy compliance.

Leads and manages software engineering teams developing scalable Java, cloud, and microservices-based products and platforms. Responsibilities include architecture leadership, hands-on development, code reviews, technical design, agile delivery, engineering quality, cloud enablement, streaming analytics, recruiting, mentoring, and stakeholder collaboration. The role oversees the full software development lifecycle and advances high-volume data access, platform strategy, and engineering productivity.

Leads software engineering projects, develops complex software solutions, researches technical alternatives, and guides daily development activities. Responsibilities include programming, proof-of-concept development, roadmap creation, quality and process adherence, third-party evaluation, and collaboration with business and technical stakeholders. Requires strong Java-stack expertise, relational database and SQL skills, software design knowledge, Agile experience, and the ability to lead distributed teams.

Develop, test, deploy, troubleshoot, and refactor software components. Build Java and Spring Boot microservices with REST APIs and SQL, adopt new technologies and architecture patterns, contribute to requirements and team decisions, and support CI/CD automation. Collaborate with peers in an Agile environment using TDD and BDD while maintaining strong security, communication, analytical, and problem-solving practices.