Top AWS Jobs in Chennai

Designs and implements scalable data architectures, ETL/ELT pipelines, data models, storage, and integrations using Databricks. Builds secure Delta Live Tables pipelines, configures Unity Catalog, enables data sharing, integrates BI tools, prepares datasets for generative AI, and optimizes cloud-based workloads. The role also requires Python and PySpark development, performance tuning, CI/CD deployment, and collaboration with stakeholders to deliver reliable, governed, and efficient data platforms.

The Data Architect will define application data requirements, models, storage, and integrations. Responsibilities include building scalable Databricks ETL/ELT and DLT pipelines, implementing Unity Catalog security and governance, optimizing cloud data workloads, developing Python and PySpark transformations, integrating BI tools, preparing GenAI datasets, and deploying pipelines through CI/CD. The role also involves troubleshooting, performance tuning, data sharing, stakeholder collaboration, and ensuring reliable, secure, and cost-efficient data platforms.

Designs and governs scalable data architectures using Databricks, including ETL/ELT pipelines, Delta Lake, DLT, Auto Loader, Unity Catalog, and Delta Sharing. Builds secure, observable, and optimized data platforms across cloud environments, develops PySpark and Python transformation logic, integrates BI tools, prepares GenAI datasets, and deploys pipelines through CI/CD. Requires strong data modeling, warehousing, performance optimization, and cloud data engineering expertise.

Design and implement scalable data architectures, ETL/ELT pipelines, and Databricks-based data platforms. Build secure Delta Live Tables workflows, configure Unity Catalog, manage data sharing and integrations, optimize performance and costs, and prepare datasets for analytics and generative AI. Collaborate with stakeholders to ensure robust data modeling, governance, observability, and reliable delivery through cloud-based CI/CD practices.

Designs, develops, and maintains scalable software solutions integrating AI and machine learning models into commercial products and internal processes. Collaborates with data scientists, product managers, and cross-functional stakeholders; writes high-quality code; reviews architectures; supports product launches and process improvements; and follows Agile, NPI, and deployment best practices.

Designs, integrates, troubleshoots, and automates enterprise infrastructure across AWS, hybrid cloud, on-premises, server, network, endpoint, and mainframe environments. Diagnoses complex technical issues, develops reliable solutions, documents architectures and procedures, coordinates cross-functional delivery, manages risks, and communicates technical recommendations to customers. The role also emphasizes continuous learning, certifications, and progression toward architecture or distinguished engineering positions.

Designs, builds, and operates Apache NiFi dataflows and integration pipelines for secure, scalable application and data integration. Responsibilities include transformation, routing, orchestration, production deployment, monitoring, troubleshooting, performance tuning, high availability, NiFi Registry lifecycle management, security, governance, and on-call support. The role also requires cloud, Kafka, scripting, Linux, CI/CD, automation, and coaching development teams.

Develop and deploy scalable enterprise applications using .NET, C#, Python, React or Angular, and multi-cloud platforms. Design APIs, microservices, event-driven integrations, and AI-enabled features while supporting Docker, Kubernetes, infrastructure as code, CI/CD, security, and performance optimization. Collaborate with architects, DevOps teams, product managers, and developers on hands-on coding, solution design, implementation, and mentorship.

Develop and support enterprise data solutions using SQL Server, Databricks, ETL pipelines, Power BI, and automation tools. Responsibilities include database development and optimization, data integration, validation, reconciliation, reporting, production support, troubleshooting, quality assurance, and process improvement. The role requires collaboration with stakeholders, support for critical data platforms and SLAs, and availability for shift operations. It is a mandatory five-day, office-based position in Bengaluru, Hyderabad, Chennai, or Coimbatore.

Develop and support enterprise data solutions using SQL Server, Databricks, ETL pipelines, Power BI, and automation tools. Responsibilities include database development and performance tuning, data integration, validation and reconciliation, production support, dashboard creation, data quality management, and process automation. The role requires troubleshooting critical data platforms, collaborating with stakeholders, supporting reporting needs, and working five days onsite from a designated Indian strategic location with Shift-B availability.

Leads the design, development, and configuration of scalable Java and Spring Boot applications. Acts as a subject matter expert, coordinates multiple teams, makes technical decisions, mentors engineers, resolves cross-team issues, and monitors project delivery. Requires expertise in microservices, REST APIs, cloud platforms, containerization, and application security, along with substantial experience managing development efforts.

Leads mainframe modernization and migration initiatives for large global clients. Develops transformation and re-platforming solutions, conducts discovery workshops, presents technical and business cases, advises executives, and partners with sales, consulting, operations, and product teams. Requires extensive mainframe expertise across legacy technologies, migration architecture, data modernization, cloud and hybrid environments, and enterprise hosting. The role also supports AI-driven modernization, technical documentation, project lifecycle management, and client relationship development.

Develop and deploy machine learning and AI solutions for risk assessment, fraud detection, customer intelligence, personalization, and predictive modeling, particularly in financial services. Translate experiments into scalable production systems, identify data-driven business opportunities, collaborate with engineering, product, and business stakeholders, prototype emerging techniques, and communicate solutions to clients. The role requires strong analytical, technical, communication, and stakeholder management skills.

Quality Engineer responsible for analyzing requirements and designing, executing, and maintaining manual and automated software testing. The role develops test plans, scenarios, cases, automation scripts, regression suites, and defect reports across frontend, backend, database, AWS, and DevOps environments. Responsibilities include collaborating with developers and stakeholders, supporting Agile and DevOps practices, researching automation technologies, preparing estimates and reports, and improving testing processes. Requires strong C# automation, Selenium, API testing, SQL, and software quality assurance experience.

Leads the design, delivery, and optimization of complex Guidewire PolicyCenter and Jutro solutions. Responsibilities include solution architecture, integrations, cloud migration, CI/CD, monitoring, performance, quality assurance, vendor coordination, Agile delivery, and technical documentation. Supervises and mentors Guidewire and Jutro engineering teams, manages capacity and performance, develops technical capabilities, and partners with stakeholders, architects, vendors, and business units to align technology solutions with enterprise objectives.

Designs, deploys, and maintains scalable cloud infrastructure using infrastructure as code, CI/CD, Kubernetes, and GitOps. Responsibilities include optimizing highly available Kubernetes platforms, implementing cloud security, monitoring Linux and Windows systems, troubleshooting infrastructure, collaborating with development and operations teams, and maintaining technical documentation.

Own the strategy, roadmap, service model, and investment priorities for an enterprise AI runtime and agentic platform. Productize GPU compute, Kubernetes, model serving, inference, agent orchestration, lifecycle management, APIs, observability, and developer self-service across private, public, and hybrid clouds. Partner with engineering, cloud, security, governance, architecture, and compliance leaders to improve platform reliability, utilization, adoption, cost efficiency, and developer experience. Influence senior stakeholders and translate complex infrastructure capabilities into consumable enterprise services.

Lead backend architecture and technical strategy for scalable enterprise SaaS solutions. Design financial systems using Java, Kotlin, DynamoDB, Pulsar, GraphQL, and big data tools. Establish engineering standards, mentor teams, guide roadmaps, and collaborate with product, engineering, UX, QA, and implementation teams. The role requires deep distributed-systems expertise, cross-functional influence, customer focus, and responsible use of AI-powered development tools.

Design and build production-grade AI-powered applications and reusable industry solutions on Genesys Cloud. Develop Architect flows, integrations, agentic workflows, Digital Teammates, and AI applications using APIs, enterprise systems, knowledge, LLMs, and orchestration technologies. Translate industry business processes into scalable solutions, lead architecture and technical design, prototype emerging capabilities, and take applications through production. Provide code reviews, mentorship, debugging, and hands-on implementation while collaborating with customers, Product, Engineering, and partners.

Analyze and modernize COBOL-based mainframe applications by converting business logic into Java applications, microservices, and cloud-ready solutions. Develop, test, deploy, document, and troubleshoot enterprise Java systems while maintaining functionality, performance, and data integrity. Collaborate with architects, business analysts, users, and testing teams throughout migration, integration, and production support activities.

Analyze and modernize COBOL mainframe applications by converting business logic into Java applications, microservices, and cloud-ready solutions. Develop, test, deploy, document, and optimize Java systems while maintaining functionality, performance, and data integrity. Collaborate with architects, analysts, business users, and testing teams; support integration testing, production deployment, troubleshooting, and post-migration activities.

Designs, develops, tests, deploys, and supports scalable software products and platform capabilities using C# and modern .NET. Builds APIs, backend services, frontend components, integrations, and AI-enabled application features in Azure. Owns capabilities through production support, modernization, monitoring, and continuous improvement. Contributes to architecture, code reviews, CI/CD, security, reliability, and technical planning while collaborating with global Product, Engineering, Architecture, Security, and Platform teams. Mentors engineers and supports maintainable, production-grade applications.

Design, develop, test, deploy, and support scalable web applications and platform capabilities. Build React and TypeScript frontends integrated with .NET and Azure services, contribute to APIs, reusable components, AI-enabled features, CI/CD, observability, security, and application modernization. Own features through production support, collaborate with cross-functional global teams, participate in technical decisions and code reviews, and mentor less experienced engineers.

Develop and maintain scalable Big Data solutions for consumer and wealth client insights. Design Hadoop-based batch and streaming workflows, optimize performance, support production incidents and releases, define enterprise data strategies, and work with stakeholders on technical requirements. The role includes using Hadoop, Spark, Scala, Python, Kafka, and NoSQL technologies, while mentoring junior engineers and contributing to end-to-end solution design and delivery.

Lead end-to-end data science solutions for cyber fraud prevention, including machine learning models, anomaly detection, risk scoring, feature engineering, data pipelines, APIs, automated decisioning, and production monitoring. The role requires advanced Python and SQL, cloud and deployment experience, model validation, operational support, technical documentation, vendor evaluations, cross-functional collaboration, and mentoring of less-experienced team members.