Top AWS Jobs in Pune

Lead design and delivery of GCP data platforms using BigQuery, Pub/Sub, and Dataflow. Architect high-volume ingestion and ETL pipelines, drive cloud migrations, mentor engineers, ensure security, cost optimization, and stakeholder alignment to deliver analytics and ML-ready data solutions.

Lead automation and platform engineering for Unix estates (RedHat, OEL, Solaris). Build and maintain Ansible playbooks, IaC pipelines, and automation frameworks; standardize builds, patching, and compliance; integrate with Git and CI/CD; drive platform modernization, performance optimization, and operational excellence while collaborating with development, security, and third parties.

Support and configure application and digital experience monitoring tools, provide operational and on-call support, automate tasks with scripts, document technical processes, and partner with engineering teams to meet internal customer monitoring needs.

Lead data engineering efforts to ingest, unify, process, and analyze large, high-dimensional datasets using cloud and big-data platforms. Partner with product, data science, and platform teams to build reusable, production-ready data solutions, prototypes, and analytics that drive cybersecurity and fraud-related products and insights.

Operate and improve multi‑cloud (AWS/Azure/hybrid) platforms with SRE practices: lead incident triage and RCA, manage Kubernetes and CI/CD pipelines, implement IaC and automation, enhance observability/AIOps, and drive DevSecOps and operational excellence across global 24x7 operations.

Lead automation and platform engineering for Unix estates (RedHat/OEL/Solaris). Design and implement Ansible-based IaC, CI/CD pipelines, standardised builds, patching and compliance. Modernise legacy operations, integrate automation with Git and service management, resolve complex platform issues, optimise capacity/performance, produce documentation and reusable patterns, and collaborate with engineering, security, and third parties using Agile practices.

Lead automation and platform engineering for Unix estates (RedHat, OEL, Solaris). Build and maintain Ansible-based IaC, CI/CD pipelines, patching and lifecycle automation, and integrate with Git and service management. Drive platform modernization, resolve complex platform issues, optimize performance and capacity, produce automation standards and documentation, and collaborate with security, development, and third parties to deliver resilient, automated services.

Design, build, automate, and optimize Mastercard/Vocalink's Windows platform using SCCM, Ansible, and IaC. Implement automated OS deployment, patching, compliance, and build pipelines; integrate with CI/CD and Git workflows. Lead platform modernization, troubleshoot complex Windows issues, and collaborate with security, infrastructure, application teams and vendors to deliver scalable, secure platform services.

Design, build, automate and optimize the Windows platform using SCCM, Ansible and IaC. Deliver OS deployment, patching, image/build automation, CI/CD integration, compliance enforcement, platform modernization, troubleshooting, capacity planning and cross-team collaboration to meet SLAs and security standards.

Design, build, and operate scalable ETL/ELT data pipelines and curated datasets for analytics and ML. Ensure reliability, performance, data quality, governance, and cost optimization across Hadoop and cloud platforms. Implement CI/CD, monitoring, data lineage, and security controls; collaborate with product, data science, and platform teams; troubleshoot production issues and participate in on-call rotations.

Designs and implements data ingestion, aggregation, and processing pipelines across Hadoop and cloud platforms to enable unified data views and analytics. Partners with product, data science, and platform teams to integrate data assets, build prototypes, and produce actionable insights and BI solutions. Applies data modeling, large-scale querying, and analytics to support security, fraud, and identity products.

Deliver live instructor-led and virtual product training and hands-on labs for customers, partners, and employees. Create and maintain technical training materials, developer labs, scripts and demos. Mentor partner delivery teams, support certification readiness, and use learner feedback and AI tools to improve course effectiveness. Travel 25–50% for training and workshops.

Manage AWS infrastructure across Prod/Stage/Dev, handle incident management and root cause analysis for core AWS services, ensure availability and performance, monitor health and cost, perform access management and resource optimization, support Terraform-based provisioning, automate operational tasks, and work with CI/CD pipelines while collaborating with Engineering, Security, and Data teams.

The Senior Software Engineer - Test will lead QA and automation testing for ecommerce payment solutions, mentor junior engineers, and drive technical decisions within Agile teams.

Lead design and implementation of full-stack web applications and scalable data pipelines. Build intuitive UIs, backend data models, performant analytics, write and review tests, mentor junior engineers, and collaborate with product and design to deliver customer-focused solutions.

Lead design and implementation of scalable, secure cloud-native data and AI platforms across AWS and Azure. Set platform strategy, governance, and best practices; build lakehouse/medallion architectures, CI/CD and IaC, batch and streaming pipelines, observability, cost optimization, and MLOps integration. Mentor engineering teams, collaborate with stakeholders, and ensure security and compliance.

The Site Reliability Engineer will ensure cloud-native system stability and performance, manage AWS infrastructure, and optimize reliability in Java microservices.

Design, build, and operate Dev Cloud and internal developer platform capabilities. Own Docker Desktop developer workflows, extend Backstage (templates, plugins, catalogs), build cloud-native services on AWS, automate IaC and CI/CD, drive observability and security, onboard application teams, troubleshoot developer issues, and mentor engineers to improve developer experience and platform reliability.

Lead and build cloud-based data pipelines and ETL/ELT workflows, translate business requirements into technical designs, manage and mentor a small team, engage directly with clients, ensure data quality and production-grade code, and contribute to solution design and project delivery using Agile practices.

Lead and scale multiple security and access management programs across engineering and cloud operations. Plan and oversee technical initiatives, collect requirements, drive automation for governance, mitigate risks, and deliver dashboards/KPIs to Executive Leadership. Advocate tooling and improve traceability for security, compliance, and risk initiatives.

Maintain uptime for a SaaS observability platform by deploying production applications, securing environments, automating infrastructure and operational tasks (Python/Terraform/Kubernetes), collaborating with developers and senior engineers, producing runbooks/documentation, and developing AI-assisted automation workflows.

Design and implement technical features, collaborate with clients, write production-ready code, ensure quality deliverables, mentor team members, and implement ML models on large scale.

Design and build production-grade AI applications embedding ML/LLM capabilities. Integrate trained models into APIs, services, UIs, and workflows. Operationalize models (versioning, deployment, monitoring), implement guardrails, ensure security/privacy/compliance, apply bias mitigation and explainability, and mentor team members on AI engineering best practices.

Develop complex solutions using various technologies, manage projects through all lifecycle phases, and collaborate with teams to drive results. Emphasizes consulting mindset, client-first approach, and effective communication skills.

Lead development and deployment of production ML models and analytics for wealth management and retail banking. Analyze large datasets, design predictive solutions (segmentation, churn, personalization, risk), build data pipelines and feature engineering, monitor model performance, drive MLOps and responsible AI practices, and communicate insights to stakeholders.