Sadhvik Chirunomula

Lead Product Engineer

Modak Analytics | Hyderabad (09/2024–Current)

• Architected a multi-tenant, cloud-native analytics platform supporting real-time distributed processing for over 10 enterprise clients, enabling sub-second insight delivery.
• Led 6+ cross-functional teams (Product, QA, Engineering, DevOps, Sales Engineering) and ensured 100% on-time feature releases across multiple product cycles.
• Reduced deployment time by 40% through automation of CI/CD pipelines, real-time observability, and integrated tooling (CLI, REST APIS, UI).
• Represented technical roadmap in 15+ customer-facing sessions, executive briefings, and industry panels, influencing roadmap alignment and stakeholder engagement.
• Delivered SaaS integrations across AWS, Azure, and GCP marketplaces, reducing onboarding time by 30% and enabling automated licensing and billing.
• Provisioned auto-scaling Apache Spark clusters using Kubernetes, Docker, and Terraform (IaC), reducing environment setup time by 75% and cutting infrastructure costs by 50%.
• Engineered secure and scalable landing zones on Google Cloud Platform (GCP) and Microsoft Azure, aligned with enterprise architecture standards to support zero-touch provisioning across 20+ projects.

Senior DevOps Engineer

Modak Analytics | Hyderabad (03/2022–08/2024)

DevOps Engineer

Modak Analytics | Hyderabad (04/2020–02/2022)

• Automated infrastructure provisioning using Terraform and integrated CI/CD pipelines via GitHub Actions and Azure DevOps, reducing deployment errors by 70% and cutting release times by 50%.
• Designed cloud cost governance frameworks, including automated billing dashboards, tagging enforcement, and budget alerting, leading to a 25-35% reduction in monthly cloud spend.
• Developed real-time observability architecture using Grafana, Prometheus, ELK Stack, Splunk, and Google Stackdriver, enabling SRE best practices and reducing MTTR by 40%.
• Delivered marketplace-ready SaaS integrations on AWS Marketplace, Azure Marketplace, and Google Cloud Marketplace, supporting automated licensing, metering, and billing.
• Automated deployment of IBM StreamSets and Confluent Kafka pipelines across Google Cloud and Azure, increasing deployment consistency and reducing failure rates by 60%.
• Built hybrid cloud deployment frameworks using Terraform, Azure DevOps, and Ansible, enabling scalable rollout across 20+ tenant environments.
• Deployed containerized microservices on Kubernetes clusters, doubling service availability and supporting multi-region failover with zero downtime deployments.
• Enabled full-stack performance observability through Splunk and Dynatrace, achieving average bottleneck resolution time under 2 hours and improving uptime.

Data Engineer

Modak Analytics | Hyderabad (09/2019–03/2020)

• Developed a custom Java-based ETL platform using StreamSets and PostgreSQL, designed to handle 1TB+ of daily data across multi-cloud environments.
• Engineered flexible pipeline execution logic supporting diverse data sources and sinks including Kafka, GCS, Amazon S3, Azure Data Lake Storage (ADLS), Oracle, and MongoDB, improving reliability and reducing integration effort.
• Automated end-to-end PaaS deployment lifecycle across AWS, Azure, and GCP, improving provisioning speed by 60% and eliminating manual configuration.