I build and debug backend systems that have to work under real-world conditions—distributed data, inconsistent inputs, high-volume workflows, and the invisible failure modes that show up when services depend on each other.

My work focuses on:

• Distributed systems architecture
• Backend system design
• Reliability engineering & observability
• Data pipelines and hydration workflows
• High-throughput event processing
• Debugging across multiple services

I care about the parts of the system where most failures actually occur: data boundaries, cross-service timing, concurrency, retries, ordering, and data aggregation.

I’ve spent my career building backend platforms for large-scale products such as:

• LTK – powering distributed notification workflows for millions of users
• MyFitnessPal – modernizing event-processing and nutrition data pipelines for 220M users
• 2U – improving content-delivery reliability across APIs, queues, caching, and search
• OSIsoft – building cloud-hosted telemetry ingestion pipelines for industrial clients

I work in the space where backend systems, product behavior, and distributed data flows intersect.

• Distributed systems & workflow orchestration
• Event-driven architectures (queues, streams, fan-out/fan-in)
• Observability (logs, metrics, traces, distributed debugging)
• Reliability patterns (retries, backoff, dedupe, idempotency)
• Data pipelines (Athena, Lambda, DynamoDB, S3, Step Functions)
• Go & Python for backend services

Languages: Go, Python, JavaScript, TypeScriptC# Cloud: AWS (Lambda, SQS, SNS, DynamoDB, Step Functions, Athena) Observability: CloudWatch, OpenTelemetry Patterns: Distributed systems, microservices, event-driven design Other: PostgreSQL, MySQL, Docker, CI/CD (GitHub Actions)

• LinkedIn: (https://linkedin.com/in/johnson-james-m)
• Email: [email protected]