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Abhishek Dimri

@abhishekdimri

Message

I’m an Amazon SDE building scalable distributed backend infrastructure with low-latency APIs and reliable pipelines.

India

Message

What I'm looking for

I’m looking for a role where I can build scalable distributed backend services and data pipelines on AWS—improving latency, reliability, and observability while iterating quickly on production-grade systems.

I’m an SDE at Amazon focused on replacing failing legacy systems with backend infrastructure that performs at scale. In production, I’ve driven results like ~30% better SLA adherence, 1,000+ concurrent agents, 10K+ requests/min, and sub-100ms p99 API latency.

My work centers on distributed task allocation, rule-driven scheduling engines, and data pipeline engineering. I designed capacity-aware routing, heartbeat-based agent activity tracking, and lifecycle management with automated skips and permission-aware filtering to achieve near-zero task loss during degraded states.

I also build for operability and iteration speed—using CloudWatch dashboards and custom metric alarms to reduce MTTD and give teams early signals before issues hit customers. Previously, I redesigned a rule-testing data workflow to cut a week-long cycle to ~30 minutes for 100GB datasets using Apache Spark, Scala, and AWS Step Functions with fault tolerance and retries.

Experience

Work history, roles, and key accomplishments

Current

Software Development Engineer

Current

Amazon Development Centre

Oct 2024 - Present (1 year 8 months)

Re-architected a legacy queue-based task allocation system into a distributed platform supporting 1,000+ concurrent agents and 10K+ requests/min, improving workflow SLA adherence by ~30%. Built a rule-driven scheduling engine and capacity-aware routing that reduced SLA breach incidents by 30% and eliminated stale-state task loss.

Distributed Systems System Design Java Scala DynamoDB AWS Step Functions AWS Cloudwatch Schedulers Capacity Aware Routing

Associate Data Engineer

IBM India Pvt. Ltd.

Jun 2024 - Oct 2024 (4 months)

Built SQL-based pipelines for enterprise data under unstable schemas by enforcing ingestion contracts to block bad data. Defined SLAs and schema agreements with stakeholders, reducing downstream incidents and ensuring predictable delivery. Applied unit tests, code reviews, and Git versioning from day one.

Scala Azure Spark Git SQL

Software Engineer Intern

Amazon Development Centre

Jan 2023 - Jul 2023 (6 months)

Redesigned rule-testing to run via a simulation service instead of full production datasets, cutting 100GB cycles from a week to ~30 minutes (99.96% reduction). Implemented multi-stage distributed pipelines on Apache Spark, Scala, and AWS Step Functions with fault tolerance and automatic retries, reducing per-change iteration time from days to hours.

Apache Spark Scala AWS Step Functions Fault Tolerance Design Patterns