Senior Data Operations Engineer

Our Global Diabetes Capability Center in Pune is expanding to serve more people living with diabetes globally. Our state-of-the-art facility is dedicated to transforming diabetes management through innovative solutions and technologies that reduce the burden of living with diabetes.

We’re a mission-driven leader in medical technology and solutions with a legacy of integrity and innovation, join our new Minimed India Hub as Senior Data Operations Engineer. We are seeking an experienced Senior DataOps Engineer to join our team. This candidate will have a strong background in DevOps, DataOps, or Cloud Engineering practices, with extensive experience in automating the CICD pipelines and modern data stack technologies.

This role offers a dynamic opportunity to join Medtronic's Diabetes business. Medtronic has announced its intention to separate the Diabetes division to promote future growth and innovation within the business and reallocate investments and resources across Medtronic, subject to applicable information and consultation requirements. While you will start your employment with Medtronic, upon establishment of SpinCo or the transition of the Diabetes business to another company, your employment may transfer to either SpinCo or the other company, at Medtronic's discretion and subject to any applicable information and consultation requirements in your jurisdiction

Responsibilities may include the following and other duties may be assigned:

• Develop and maintain robust, scalable data pipelines and infrastructure automation workflows using GitHub, AWS, and Databricks.
• Implement and manage CI/CD pipelines using GitHub Actions and GitLab CI/CD for automated infrastructure deployment, testing, and validation.
• Deploy and manage Databricks LLM Runtime or custom Hugging Face models within Databricks notebooks and model serving endpoints.
• Manage and optimize Cloud Infrastructure costs, usage, and performance through tagging policies, right-sizing EC2 instances, storage tiering strategies, and auto-scaling.
• Set up infrastructure observability and performance dashboards using AWS CloudWatch for real-time insights into cloud resources and data pipelines.
• Develop and manage Terraform or CloudFormation modules to automate infrastructure provisioning across AWS accounts and environments.
• Implement and enforce cloud security policies, IAM roles, encryption mechanisms (KMS), and compliance configurations.
• Administer Databricks Workspaces, clusters, access controls, and integrations with Cloud Storage and identity providers.
• Enforce DevSecOps practices for infrastructure-as-code, ensuring all changes are peer-reviewed, tested, and compliant with internal security policies.
• Coordinate cloud software releases, patching schedules, and vulnerability remediations using Systems Manager Patch Manage.
• Automate AWS housekeeping and operational tasks such as:
• Cleanup of unused EBS Volumes, snapshots, old AMIs
• Rotation of secrets and credentials using secrets manager
• Log retention enforcement using S3 Lifecycle policies and CloudWatch Log groups
• Perform incident response, disaster recovery planning, and post-mortem analysis for operational outages.
• Collaborate with cross-functional teams including Data Scientists, Data Engineers, and other stakeholders to gather, implement the infrastructure and data requirements.

Required Knowledge and Experience:

• 8+ years of experience in DataOps / CloudOps / DevOps roles, with strong focus on infrastructure automation, data pipeline operations, observability, and cloud administration.
• Strong proficiency in at least one Scripting language (e.g., Python, Bash) and one infrastructure-as-code tool (e.g., Terraform, CloudFormation) for building automation scripts for AWS resource cleanup, tagging enforcement, monitoring and backups.
• Hands-on experience integrating and operationalizing LLMs in production pipelines, including prompt management, caching, token-tracking, and post-processing.
• Deep hands-on experience with AWS Services, including
• Core: EC2, S3, RDS, CloudWatch, IAM, Lambda, VPC
• Data Services: Athena, Glue, MSK, Redshift
• Security: KMS, IAM, Config, CloudTrail, Secrets Manager
• Operational: Auto Scaling, Systems Manager, CloudFormation/Terraform
• Machine Learning/AI: Bedrock, SageMaker, OpenSearch serverless
• Working knowledge of Databricks, including:
• Cluster and workspace management, job orchestration
• Integration with AWS Storage and identity (IAM passthrough)
• Experience deploying and managing CI/CD workflows using GitHub Actions, GitLab CI, or AWS CodePipeline.
• Strong understanding of cloud networking, including VPC Peering, Transit Gateway, security groups, and private link setup.
• Familiarity with container orchestration platforms (e.g., Kubernetes, ECS) for deploying platform tools and services.
• Strong understanding of data modeling, data warehousing concepts, and AI/ML Lifecycle management.
• Knowledge of cost optimization strategies across compute, storage, and network layers.
• Experience with data governance, logging, and compliance practices in cloud environments (e.g., SOC2, HIPAA, GDPR)
• Bonus: Exposure to LangChain, Prompt Engineering frameworks, Retrieval Augmented Generation (RAG), and vector database integration (AWS OpenSearch, Pinecone, Milvus, etc.)