Staff Data Platform Engineer (AWS, Databricks, Azure, IaC, Solution Architect, Java/Python, 6 - 10 Years)

Overview

Build, implement, and operate enterprise-grade cloud-based data platform capabilities supporting the migration of analytical and AI/ML workloads from open-source Hadoop platforms to AWS, Azure, and Databricks. Work with Architecture, Security, Product, and Engineering teams to deliver scalable, secure, reliable, and operationally efficient solutions.

What you'll do

• Design, develop, and maintain scalable, secure, and reliable cloud-based data platform services across AWS, Azure, and Databricks.
• Collaborate with Architecture, Product, Security, and Engineering teams to implement enterprise-grade cloud data platform solutions.
• Build and enhance reusable platform capabilities, self-service onboarding solutions, and engineering frameworks that accelerate cloud adoption.
• Implement data integration pipelines and processing frameworks to ingest, transform, and manage large volumes of structured and unstructured data.
• Support migration and modernization of data, analytics, and AI/ML workloads from Hadoop-based platforms to AWS, Azure, and Databricks.
• Automate infrastructure provisioning, platform deployment, and operational processes using Infrastructure-as-Code tools such as Terraform and CloudFormation.
• Implement and support data governance, metadata management, lineage, security, and access management capabilities across cloud platforms.
• Monitor and optimize platform performance, scalability, reliability, and cost efficiency across AWS, Azure, and Databricks environments.
• Partner with product and application teams to onboard workloads and enable adoption of cloud platform capabilities.
• Troubleshoot complex production issues and drive continuous improvement in platform reliability and operational excellence.
• Stay current with emerging cloud, data, and platform engineering technologies and recommend improvements where appropriate.
• Provide technical guidance and mentorship to engineers while promoting engineering best practices and operational rigor.

What you'll need

• 8+ years of experience in Cloud Data Engineering, Big Data Engineering, Platform Engineering, or Data Platform Engineering.
• Strong hands-on experience building and operating enterprise-scale cloud data platforms.
• Strong expertise in cloud data platform services across AWS and Azure, including AWS EMR, EMR on EKS, Glue, Athena, S3, IAM, Lake Formation, and Azure services such as ADLS, Azure Databricks, Synapse Analytics, Data Factory, Azure Kubernetes Service, and Azure identity and access management.
• Hands-on experience with Databricks, Delta Lake, Unity Catalog, and Lakehouse architecture patterns.
• Hands-on experience designing and operating data platform solutions on at least one major cloud platform, with preference for AWS, Azure, or both.
• Experience migrating workloads from Hadoop-based platforms to cloud environments.
• Strong proficiency in Python, Scala, or Java.
• Hands-on experience with Infrastructure-as-Code tools such as Terraform or CloudFormation.
• Strong expertise in Spark, Hive, Hadoop ecosystem technologies, and distributed data processing frameworks.
• Experience implementing automation, CI/CD, and platform engineering best practices.
• Strong understanding of data governance, security, compliance, metadata management, and access management controls.
• Strong Linux, operating system, networking, and troubleshooting skills.
• Excellent problem-solving, communication, collaboration, and stakeholder management skills.
• Experience working with architecture teams and translating enterprise architecture designs into scalable, production-ready implementations.

Nice to have

• Experience building and operating multi-tenant enterprise data platforms.
• Experience with Kubernetes, EKS, containerized workloads, and modern platform engineering practices.
• Experience implementing observability, monitoring, logging, alerting, and reliability engineering solutions.
• Experience with cost governance and cloud optimization initiatives.
• Experience supporting AI/ML platforms and data science workloads.
• Experience mentoring engineers and driving engineering best practices across teams.
• Experience working on large-scale cloud transformation or modernization programs.

Details

• Location: Bengaluru, India.