Open to opportunities

sangati anuradha

@sangatianuradha

Message

Platform Engineer specializing in DevOps automation and cloud-based data platform reliability.

India

Message

What I'm looking for

I’m looking for a Platform/DevOps role where I can automate and modernize cloud-based data platforms—owning Terraform/Kubernetes, CI/CD with Harness, Airflow orchestration, Databricks deployments, and production monitoring to improve reliability and scalability.

I’m a Platform Engineer with 4+ years of IT experience, including 2+ years of hands-on Platform Engineering and DevOps. I build reliable cloud platforms using Terraform, Kubernetes (AKS), Docker, Harness CI/CD, Airflow, and Azure Databricks, with a strong focus on automation and operational resilience.

Most recently at Publicis Sapient, I supported cloud-based data platform modernization for Capital Group—migrating legacy MFT to Docker Registry and AKS, modernizing CI/CD (Bamboo to Harness), upgrading AKS clusters (1.27 to 1.35), orchestrating Airflow workloads on AKS, enabling Databricks deployment with Asset Bundles (DBX), and improving production visibility with Datadog monitoring. Previously as a Big Data Developer, I delivered Spark/Java-based systems on AWS EMR/S3/Athena and helped reduce batch processing time significantly while migrating legacy workloads to a Big Data cloud environment.

Experience

Work history, roles, and key accomplishments

Current

Platform Developer

Current

Publicis Sapient

Apr 2024 - Present (2 years 3 months)

Worked as a Platform Developer supporting cloud-based data platform modernization and operational reliability. Contributed to legacy MFT migration, CI/CD pipeline modernization, AKS cluster upgrades, Airflow workload orchestration, Databricks deployment enablement, and Datadog monitoring.

Terraform Kubernetes Airflow AKS Databricks Asset Bundles Datadog AWS Lambda AKS Upgrades Workflow Orchestration

Big Data Developer

TechStar IT Services Pvt Ltd

Aug 2021 - Aug 2022 (1 year)

Built and supported a Big Data payment processing system handling 20+ million customer records. Helped migrate a legacy payment system to a Big Data environment, reducing batch processing time from 84 hours to 27 hours, and supported migration from Cloudera to AWS services, reducing processing time by 12 hours.