Jagadesh Ata — Senior Go Backend / Kubernetes Platform Engineer
I build healthcare interoperability platforms in Go: FHIR R4 APIs, HL7 v2 to FHIR integration services, and Kubernetes-native systems that stay predictable in production. My focus is correctness, traceability, and operational clarity for real clinical data.
Target roles / focus: Senior Kubernetes Platform Engineer (Golang/Python API) | Kubernetes Engineer (Golang/Python API) | DevOps Engineer II (Go/Python Automation & CI/CD) | Go backend / Golang developer.
Best way to connect: If you’re hiring for these roles, use the contact form or ping LinkedIn. Email alias:hello [at] jagadesh [dot] dev.
Role Fit
- Senior Go backend engineering for high-throughput APIs and data pipelines.
- Healthcare interoperability across FHIR R4, HL7 v2, and clinical data exchange workflows.
- Kubernetes Go development (CRDs, controllers, operators) for platform reliability and automation.
Enterprise-Ready Capabilities
| Capability | What it means in production |
|---|---|
| Interoperability correctness | Versioned APIs, strict validation against profiles/IGs, and consistent data lineage. |
| Reliability and observability | End-to-end tracing, metrics, and logs that can explain any clinical event. |
| Security for PHI | OAuth2/OIDC, RBAC, NetworkPolicies, and least-privilege access. |
| Platform delivery | Cloud-agnostic Kubernetes deployments with GitOps and predictable releases. |
Technical Depth
FHIR R4 and HL7 v2 Integration
- Search, pagination, Bundles/transactions, and conditional create/update behavior aligned to real-world FHIR patterns.
- HL7 v2 translation with mapping, normalization, enrichment, and audit-ready lineage.
- Idempotent ingestion and replayability with correlation IDs for end-to-end traceability.
Go API Engineering
- REST and gRPC services with OpenAPI specs, contract tests, and clear error behavior.
- Concurrency patterns with pprof-driven tuning and practical performance guardrails.
- API versioning and schema evolution designed for long-lived healthcare integrations.
Kubernetes-Native Go Development
- CRDs, controllers, and operators using controller-runtime and operator-sdk.
- Golden-path automation to remove toil and enforce production standards.
- GitOps pipelines for repeatable delivery across AWS, Azure, and GCP.
Selected Outcomes
Metrics are normalized to protect client confidentiality while preserving directional impact.
- FHIR API performance tuning: p95 latency improved 180ms -> 95ms in normalized benchmarks | reduced incident volume and protected API SLOs.
- Replay-safe HL7 v2 to FHIR ingestion: duplicate encounter writes prevented during retry storms | improved billing accuracy and downstream data trust.
- Tracing + structured logs rollout: triage time reduced 35% in incident drills | faster MTTR during production events.
- Multi-cloud interoperability reliability: p99 error-budget burn reduced quarter-over-quarter | fewer customer-visible degradations.
- Kubernetes delivery hardening: change failure rate trended down while deployment frequency increased | faster feature delivery with lower rollback risk.
Experience Snapshot
- Anthem, Inc. — Senior Kubernetes Platform Engineer (Golang/Python API)
- Farmers Insurance — Kubernetes Engineer (Golang/Python API)
- Bayer — DevOps Engineer II (Go/Python Automation & CI/CD)
Core stack: Go Kubernetes/OpenShift FHIR R4 HL7 v2 gRPC/REST CI/CD IaC
Case Studies
Mini Case Study: Replay-Safe HL7 v2 to FHIR Ingestion
- Problem: ADT retries and out-of-order delivery produced duplicate encounters and noisy reconciliation queues.
- Method: Implemented correlation IDs, idempotency keys, deterministic mapping rules, and replay-safe write guards with audit trails.
- Result: Duplicate writes reduced by ~92% in normalized replay tests, reconciliation exceptions reduced by 28%, and incident triage time reduced by 35%.
Mini Case Study: Go Service Performance Tuning + SLO Protection
- Problem: API p95 latency spikes during peak windows triggered SLO burn and on-call escalations.
- Method: Profiled hot paths with
pprof, reduced lock contention in critical handlers, tuned connection pooling, and added request-budget alerts tied to p95/p99 thresholds. - Result: p95 latency improved from ~210ms to ~120ms and p99 from ~480ms to ~260ms in normalized load tests | sustained throughput capacity improved by ~55% and error-budget burn reduced by ~40%.
Articles
- How I Design Replay-Safe HL7 v2 -> FHIR Ingestion
- Go and Kubernetes: Building Cloud-Native Platform Tools
- Building Kubernetes Operators in Go
- Kubernetes Distribution Comparison Guide
- View All Articles
Publishing Cadence (Every 30 Days)
- Publish one new engineering post every 30 days.
- Next post: FHIR IG validation + versioning in production (target: 2026-04-08).
- Following post: Controller/operator safety patterns (target: 2026-05-08).
- Keep every post tagged with date + topic to make recency obvious for recruiters.
Profile Sync Discipline
- Any LinkedIn title or keyword change gets mirrored on this site the same day.
- Quarterly review removes tooling/topics I no longer want inbound recruiter traffic for.
- Selected Outcomes gets refreshed with current metrics after major deliverables.
Contact
If you’re hiring for the target roles above, use the contact form or ping me on LinkedIn.
- Email alias:
hello [at] jagadesh [dot] dev - LinkedIn: linkedin.com/in/egntuywbw001