Manikar Kondu
Data Engineer @ Amazon Web Services- Billing Data | Data Pipelines & Big Data | Apache Spark, Kafka, Airflow, Snowflake | Data Modeling, ETL, Cloud Warehousing | AWS, GCP, Azure
- Role
- Data Engineer at Amazon Web Services (AWS)
- Location
- Seattle, WA, US
- LinkedIn followers
- 500 followers
About Manikar Kondu
I’m currently an Data Engineer on the AWS Metering team, which is responsible for processing over 450GB of uncompressed usage data per second. Our systems form the backbone of AWS Billing — collecting, transforming, and aggregating metering data for all AWS services.On the team, I’ve led and contributed to numerous high-impact projects focused on cost savings, performance optimization, and anomaly detection at scale. I regularly work on large-scale, highly available distributed systems and specialize in big data processing using technologies like EMR, Spark, and Hadoop.My work directly impacts how AWS customers receive and understand their bills — ensuring accuracy, efficiency, and reliability.
Experience
Data Engineer
Oct 2022 — Present · Seattle, WA, US
Supported the AWS Metering platform, a large-scale distributed record processing pipeline handling millions of records per second, ensuring high availability and operational reliability.• Designed and implemented new ETL and pipeline components, improving efficiency, scalability, and fault tolerance across metering services. • Migrated a key service to Native AWS (NAWS), enhancing scalability, reliability, and operational efficiency in line with Amazon’s strategic initiatives.• Orchestrated cross-region migrations, maintaining service parity, minimizing downtime, and ensuring seamless data availability.• Participated in monthly on-call rotations, resolving multiple sev2 incidents per week, mitigating cascading failures, and providing timely responses to customer issues.
Education
Missouri State University
Masters in Science , Computer Science
Jawaharlal Nehru Technological University
Bachelor's of Technology, Computer Science and Engineering
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