Deva Kishore Reddy Sangam

About Deva Kishore Reddy Sangam

I’m a seasoned Data Engineer with 9+ years of hands-on experience designing, building, and optimizing data platforms, log ingestion frameworks, and analytics systems across cloud-native (AWS & GCP) and hybrid infrastructures. I specialize in building scalable and fault-tolerant ETL/ELT pipelines, automating infrastructure with Terraform and Ansible, and orchestrating data workflows using tools like Apache Airflow, Dagster, and PySpark. With a strong foundation in Python, SQL, Java, and TypeScript, I have a proven track record of solving complex data engineering challenges in enterprise environments. Cloud Expertise: AWS: ECS, EKS, Lambda, EC2, S3, IAM, CloudWatch GCP: BigQuery, Dataflow, Pub/Sub, Cloud Functions, Cloud Monitoring Key Strengths: Designing high-throughput, real-time and batch data ingestion pipelines Processing complex paginated APIs & nested JSON data Implementing observability using Prometheus, Grafana, GCP Monitoring Creating secure, production-ready deployments with IAM, KMS, and CI/CD Supporting cross-functional DevOps and ML teams in Agile environments Transforming raw log and telemetry data into actionable business intelligence Throughout my career, I’ve delivered resilient solutions for global organizations such as American Family Insurance, Ford Motor Company, Ascena Retail, and Mayo Clinic, contributing to business-critical initiatives like predictive analytics, manufacturing optimization, and log intelligence platforms. I\'m passionate about creating intelligent data ecosystems that scale, self-heal, and empower analytics teams with high-quality data. Always learning, always building — I love solving real-world data problems with clean architecture and cloud-first thinking.

Experience

1. Data Scientist

   AmFamRe

   Apr 2023 — Present · WI, US

   Project: Intelligent Log Analytics & Scalable Data Infrastructure • Built a fault-tolerant log ingestion pipeline using AWS Firehose, Lambda, and S3 for scalable log capture from distributed systems.• Developed Terraform modules to provision complete logging environments, including EC2 instances, IAM roles, and EKS clusters.• Automated the deployment and update process of ETL pipelines using GitLab CI/CD, reducing deployment cycle time by 50%.• Integrated Ansible playbooks for configuration management, ensuring uniform environment setup across Linux servers.• Implemented real-time monitoring and alerting with Prometheus and Grafana, significantly reducing MTTR.• Ingested multi-format logs (JSON, XML, CSV) from over 15+ sources and unified data into a central S3-based data lake.• Collaborated with security teams to apply IAM-based access control and encryption across all ingestion touchpoints.• Conducted weekly infrastructure reviews, reducing cloud cost by optimizing under-utilized EC2 and storage configurations.• Coordinated cross-functional testing and user acceptance for log platform upgrades with minimal service disruption.• Authored platform documentation and runbooks, contributing to a robust knowledge base for DevOps teams.• Extended GCP involvement: Developed GCP BigQuery datasets and scheduled jobs for querying normalized log data.• Used GCP Pub/Sub and Cloud Functions to prototype log ingestion workflows for comparison against AWS pipelines.• Integrated GCP Monitoring with Slack alerts to mirror multi-cloud observability across both AWS and GCP regions