Refactor CV content for clarity and impact; update PDF version
All checks were successful
CI / build-check (push) Has been skipped
CI / build-and-push (push) Successful in 3m51s

This commit is contained in:
Nik Afiq 2026-04-09 19:55:23 +09:00
parent f640c90b5f
commit 1fc99ca403
2 changed files with 37 additions and 35 deletions

View File

@ -8,16 +8,18 @@ nik@nik4nao.com | github.com/nikafiq | nik4nao.com
## PROFESSIONAL SUMMARY
Backend engineer with 3 years of professional experience designing,
building, and operating distributed backend systems on GCP and AWS.
Strong in Go and Python, with hands-on production experience in
high-throughput event-driven services, Kafka-based pipelines,
Kubernetes, and cloud-native data platforms. Experienced in designing
systems with strict reliability, ordering, idempotency, retry safety,
and production-safe migration requirements. Applies AI/LLM tools with
deliberate guardrails in daily workflows. Trilingual in English,
Japanese (JLPT N1), and Malay. Strong typed-language foundation and
able to ramp quickly into Java backend development.
Backend engineer with 3 years of professional experience building and
operating Go-based distributed backend systems on GCP and AWS. Strong
ownership mindset with end-to-end responsibility across architecture,
implementation, deployment, production reliability, and continuous
improvement. Known for mechanism-driven problem solving, clear
technical documentation, and open knowledge sharing across teams.
Hands-on production experience with high-throughput event-driven
microservices, Kafka-based pipelines, Kubernetes, and cloud-native data
platforms. Experienced in designing systems with strict reliability,
ordering, idempotency, retry safety, security, and production-safe
migration requirements. Applies AI/LLM tools with deliberate guardrails
in daily workflows. Trilingual in English, Japanese (JLPT N1), and Malay.
---
@ -41,7 +43,7 @@ able to ramp quickly into Java backend development.
- Built cloud-native platforms across GCP, AWS, and Azure using
Kubernetes, ECS/Fargate, Lambda, Aurora, DynamoDB, and Kafka.
- Bilingual/trilingual engineer (EN/JA/Malay) with daily
- Trilingual engineer (English/Japanese/Malay) with daily
cross-functional communication across Japanese and overseas teams.
@ -57,28 +59,29 @@ next-generation carrier messaging platform initiative. Designing and
operating a distributed GCP/GKE backend pipeline bridging high-volume
upstream message delivery with a downstream consent fulfillment API.
- Proposed and led adoption of a Kafka-based queuing architecture;
designed the end-to-end pipeline with GKE, Managed Kafka
(8 partitions keyed by account_id), and Cloud Spanner under a
1500 TPS downstream global cap with strict per-account_id ordering
- Designed system architecture and selected Kafka as the messaging
backbone based on ordering, reliability, and scalability requirements
under a 1500 TPS downstream global cap
- Designed request coalescing with singleflight, reliable offset commit
ordering (offsets committed only after durable Spanner writes),
graceful shutdown, and a cronjob-based retry pipeline — achieving
at-least-once delivery with no data loss on crash
- Refactored the user-info-fetch API (a separate Spanner read service
accessed by the Gateway aggregator team at 1500 TPS): guided a junior
engineer through initial implementation, then led a full refactor
introducing hashed phone number lookup, removing non-indexed searches,
and tuning indexes — cutting CPU usage by ~30% under sustained load
- Led Locust performance testing at 120 TPS steady and 600 TPS burst;
used results to right-size GKE CPU and memory for stable production
behavior
- Designed OpenTelemetry + Datadog + Wiz observability stack; built CI
controls with semantic version tag enforcement and least-privilege
Workload Identity
- Led TDD adoption, authored team dev guidelines, identified and
escalated a 1-month deadline slip, and stepped up as informal tech
lead during a leadership gap
- Proposed and implemented hashed phone number lookup in Spanner to
avoid access hotspots, eliminate non-indexed searches, and improve
CPU efficiency under sustained load
- Improved team development efficiency by optimizing GitHub Actions
CI/CD workflows, scoping full test runs to pull requests, improving
build cache usage, and reducing unnecessary image builds to shorten
feedback cycles
- Designed observability for distributed services using OpenTelemetry,
Datadog, and tracing to improve production visibility and incident
response
- Authored architecture and design documents, including Kafka adoption
rationale and request coalescing design, to align teams through clear
written mechanisms
- Strengthened security and compliance posture by designing logs to mask
PII, implementing secure service-to-service authentication with
Workload Identity, and enforcing least-privilege access controls
- Applied AI tools (Copilot, Claude, Gemini, ChatGPT) in daily
workflows with deliberate guardrails: output validated through testing
and review, AI excluded from security-sensitive logic
@ -115,11 +118,11 @@ Azure-based delivery.
| Category | Details |
|---|---|
| **Languages** | Go, Python, TypeScript/JavaScript, Java (learning; strong typed-language foundation) |
| **Backend** | Distributed systems, event-driven architecture, REST APIs, pub/sub, concurrency, retry design, idempotency, fault tolerance |
| **Cloud — AWS** | ECS/Fargate, Lambda, Aurora/RDS, DynamoDB, Glue, CDK, CodePipeline, Bedrock, Secrets Manager |
| **Languages** | Go, Python, TypeScript/JavaScript |
| **Backend** | Distributed systems, event-driven architecture, microservices, REST APIs, pub/sub, concurrency, retry design, idempotency, fault tolerance, familiarity with Protocol Buffers and gRPC through personal projects |
| **Cloud — GCP** | GKE, Cloud Spanner, Managed Kafka, BigQuery, Cloud Trace |
| **Cloud — Azure** | Web Apps, ADB2C, Azure Pipelines |
| **Cloud — AWS** | ECS/Fargate, Lambda, Aurora/RDS, DynamoDB, Glue, CDK, CodePipeline, Bedrock, Secrets Manager |
| **Cloud — Azure** | Web Apps, Azure AD B2C, Azure Pipelines |
| **Data** | MySQL, Aurora, PostgreSQL, DynamoDB, Cloud Spanner, Kafka, Redis |
| **DevOps** | Docker, Kubernetes, ArgoCD, CI/CD, IaC (Terraform, AWS CDK, Ansible) |
| **Observability** | OpenTelemetry, Datadog, distributed tracing |
@ -139,8 +142,7 @@ Azure-based delivery.
| 基本情報技術者試験 (FE) — IPA Fundamental IT Engineer | Aug 2024 |
| JLPT N1 — Japanese Language Proficiency | Dec 2022 |
*In progress: AWS Solutions Architect Professional (SAP),
Applied Information Technology Engineer (AP)*
*In progress: Applied Information Technology Engineer (AP)*
---

Binary file not shown.