Top Engineering Jobs in Pune

Leads software engineering teams developing and operating large-scale Java-based payment network services. Responsibilities include people leadership, hiring, coaching, architecture and delivery oversight, automation, resilience and performance testing, CI/CD, observability, quality gates, operational readiness, and stakeholder communication across authorization, clearing, tokenization, and transaction-processing platforms.

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.

Leads two software engineering teams while splitting time among technical leadership, people management, and recruiting. Responsibilities include code reviews, technical backlog ownership, technology debt reduction, architecture review, production support, operational readiness, infrastructure coordination, and continuous refactoring. Requires hands-on expertise in Java, J2EE, Spring, Spring Boot, RESTful web services, event-driven architecture, scalable web services, and vulnerability remediation.

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.

Leads software engineering squads delivering secure, scalable, highly available payment-network solutions. Manages team development, hiring, performance, capacity, delivery, quality, and production outcomes. Guides Java and Spring Boot microservices, REST APIs, Kafka integrations, event-driven architecture, testing, CI/CD, observability, resiliency, and cloud-native practices. Partners cross-functionally on priorities, risks, dependencies, and technical decisions while communicating status and driving continuous improvement.

Manages and coaches multiple software engineering teams developing cloud-native B2B payment platforms, microservices, and web applications. Responsibilities include talent management, technical leadership, architecture, code quality, security, vulnerability management, testing, performance optimization, platform capacity, CI/CD automation, release workflows, incident mitigation, and engineering productivity. The role partners with product and business stakeholders, manages budgets, addresses technical debt, and ensures reliable, scalable, compliant software delivery.

Configure and maintain enterprise IAM platforms and directory services. Diagnose authentication and platform performance issues, implement API integrations and automation scripts, create technical documentation and runbooks, test secure identity protocols, and validate platform upgrades and security patches in non-production environments.

Manage and mentor a cross-functional engineering team to design, build, and deploy analytics and AI-driven full-stack solutions. Lead technical direction, architect scalable data pipelines and APIs, collaborate with product and design, and champion cloud-native, testable, production-grade applications while promoting continuous improvement and responsible AI practices.

Lead design and delivery of modern, secure, scalable cloud-native data platforms (Lakehouse) across AWS and Azure. Drive DevOps/IaC, data governance, medallion architecture, performance and cost optimization, mentor global engineers, and collaborate with stakeholders to translate business requirements into production data solutions.

Lead and manage a software engineering team to design, develop, and deliver backend solutions. Define technical direction, drive cross-department initiatives, partner with business stakeholders, manage budget/resources, enforce processes, and ensure timely, high-quality delivery using microservices, event-driven architectures, CI/CD, containerization and cloud-native platforms.

Leads a software engineering team while balancing technical, managerial, and recruiting responsibilities. Oversees planning, production support, enhancements, development, code reviews, technical backlogs, technical debt, refactoring, architecture collaboration, operations readiness, and 24/7 product support. Requires hands-on expertise in Java, J2EE, Spring, Spring Boot, RESTful services, event-driven architecture, Angular, scalable web services, vulnerability remediation, and AI-driven development practices.

Lead and grow agile engineering teams to design, build, and operate large-scale, distributed payment systems. Provide hands-on technical leadership across architecture, code quality, testing, CI/CD, security, and cloud-native deployments while partnering with product and program teams to ensure predictable, high-quality delivery.

Leads engineering strategy and delivery for a high-volume fraud detection platform. Manages cross-functional software teams, mentors engineers, oversees the full development lifecycle, and drives DevOps, CI/CD, observability, reliability, incident response, and continuous improvement. Partners with product and business stakeholders on roadmaps, budgets, and priorities while communicating technical direction to executives. Requires expertise in scalable distributed systems, cloud infrastructure, secure architecture, digital payments, and engineering transformation.

Leads Mastercard’s global software engineering organization, setting technology strategy and roadmaps for enterprise-scale configuration, onboarding, validation, certification, and lifecycle platforms. Oversees modernization, digital transformation, product delivery, engineering excellence, security, reliability, AI adoption, budgets, and organizational development. Partners with product, business, security, architecture, and executive stakeholders to deliver scalable, secure, high-performing platforms and measurable business outcomes.

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.

Designs and maintains enterprise IAM platforms and directory services, develops API integrations and automation, analyzes authentication telemetry and logs, creates technical architectures and runbooks, validates upgrades and security patches, and tests secure identity protocols for enterprise solutions.

Leads Mastercard’s Pune technology hub and serves as the local leadership point for site colleagues. Coordinates technology delivery, budgets, timelines, resources, Agile execution, architecture, resilience, security, automation, and platform initiatives. Builds relationships with senior leaders, vendors, partners, regulators, and support teams while driving employee engagement, hiring, retention, innovation, continuous improvement, and strategic alignment across distributed technology teams.

Leads a global Kubernetes platform engineering team, setting the platform roadmap and overseeing enterprise-scale infrastructure health, security, compliance, automation, observability, and scalability. Partners with FinOps, Finance, DevOps, and product leaders to manage budgets, forecast growth, optimize cloud resources, reduce operational toil, and align platform performance with business value. Develops engineering talent and drives organizational adoption of Infrastructure as Code and automated CI/CD practices.

Leads the strategic design and evolution of enterprise identity and access management platforms. Builds automated deployment pipelines and API integrations, analyzes platform telemetry and security logs, engineers defenses against architectural vulnerabilities, supports cloud migrations and compliance mandates, resolves critical identity platform outages, and evaluates zero-trust and emerging identity technologies.

Lead and grow a full‑stack engineering team for IdentityIQ, driving feature development, platform modernization, QA and test automation, and cross‑functional delivery while partnering with Product Management to scope, prioritize, and release secure, scalable enterprise identity solutions.

Lead and manage seat-structure product development teams to meet government and OEM standards, oversee design releases and engineering changes, ensure schedule and budget adherence, liaise with customers and suppliers, document lessons learned, recruit and coach engineers, and maintain safety and quality processes.

Leads software engineering teams responsible for building, modernizing, and operating a global, multi-tenant rewards platform. Responsibilities include people leadership, service ownership, delivery planning, technical guidance, production readiness, incident resolution, reliability, security, observability, cloud modernization, agile execution, and stakeholder collaboration. The role drives engineering quality, operational excellence, automation, documentation, and improvements to DORA metrics across high-volume platform services.

The role involves managing a software engineering team, promoting best practices, mentoring engineers, and collaborating on product solutions. Requires experience in Go, Unit Testing, and Agile methodologies.

Lead GBSC data engineering and analytics initiatives: design data/ETL infrastructure, implement automation, enable large-scale structured and unstructured data analysis, manage team delivery, and communicate insights to influence business decisions.

Lead ML engineering for Operational Intelligence: design and productionize multimodal transformer and agentic systems, build scalable RAG/Graph-RAG and LLMOps/MLOps pipelines, implement inference services and memory/state subsystems, apply traditional and deep learning methods, enforce Responsible AI, and drive research-to-production innovation.