Updated CV

content/cv.md

@@ -8,16 +8,41 @@ nik@nik4nao.com | github.com/nikafiq | nik4nao.com
 
 ## PROFESSIONAL SUMMARY
 
-Backend engineer with 3 years of professional experience designing and
+Backend engineer with 3 years of professional experience designing,
-operating distributed, high-throughput systems on GCP and AWS. Core
+building, and operating distributed backend systems on GCP and AWS.
-expertise in Go and Python, with hands-on production experience in
+Strong in Go and Python, with hands-on production experience in
-event-driven microservices, Kafka-based pipelines, Kubernetes, and
+high-throughput event-driven services, Kafka-based pipelines,
-cloud-native data infrastructure. Comfortable operating systems at
+Kubernetes, and cloud-native data platforms. Experienced in designing
-hundreds of TPS with reliability and zero-downtime migration
+systems with strict reliability, ordering, idempotency, retry safety,
-constraints. Trilingual (English, Japanese N1, Malay) — routinely
+and production-safe migration requirements. Applies AI/LLM tools with
-bridges Japanese and overseas engineering teams. Actively integrates
+deliberate guardrails in daily workflows. Trilingual in English,
-AI tooling (GitHub Copilot, Gemini, Claude) into daily coding,
+Japanese (JLPT N1), and Malay. Strong typed-language foundation and
-review, and documentation workflows.
+able to ramp quickly into Java backend development.
+
+
+---
+
+## SELECTED HIGHLIGHTS
+
+- Designed and operated a Kafka + GKE + Cloud Spanner backend pipeline
+  for correctness-sensitive, high-throughput user data synchronization
+  with per-account_id ordering, at-least-once delivery, and durable
+  retry handling.
+
+- Architected event-driven backend services under constraints including
+  100–120 TPS steady load, 600 TPS burst, 1500 TPS downstream cap, and
+  1500 TPS sustained Spanner read traffic across two production services.
+
+- Achieved ~30% fewer duplicate downstream calls via singleflight
+  coalescing; separately refactored a 1500 TPS Spanner read service
+  (hashed phone number lookup, removed non-indexed searches), cutting
+  CPU by ~30%.
+
+- 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
+  cross-functional communication across Japanese and overseas teams.
 
 
 ---
@@ -27,98 +52,79 @@ review, and documentation workflows.
 ### 株式会社ホープス (Hopes Co., Ltd.) — Tokyo
 **Backend Engineer** | Aug 2025 – Present
 
-Designing and operating a distributed consent management pipeline on
+Dispatched to a major domestic telecommunications carrier as part of a
-GCP/GKE connecting a high-traffic notification delivery system to a
+next-generation carrier messaging platform initiative. Designing and
-downstream fulfillment API.
+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
+- Proposed and led adoption of a Kafka-based queuing architecture;
-  to handle concurrent notification fan-out, identifying it as the
+  designed the end-to-end pipeline with GKE, Managed Kafka
-  correct solution for account_id ordering under 20–40 TPS load
+  (8 partitions keyed by account_id), and Cloud Spanner under a
-- Designed the request coalescing strategy using singleflight to
+  1500 TPS downstream global cap with strict per-account_id ordering
-  suppress duplicate in-flight downstream calls per account_id
+- Designed request coalescing with singleflight, reliable offset commit
-- Architected the full event-driven pipeline: GKE + Managed Kafka
+  ordering (offsets committed only after durable Spanner writes),
-  (8 partitions, keyed by account_id) + Cloud Spanner, with a
+  graceful shutdown, and a cronjob-based retry pipeline — achieving
-  200 TPS global cap and 10-second downstream timeout budget
+  at-least-once delivery with no data loss on crash
-- Designed graceful shutdown sequence for the consumer service,
+- Refactored the user-info-fetch API (a separate Spanner read service
-  ensuring in-flight requests complete cleanly before pod termination
+  accessed by the Gateway aggregator team at 1500 TPS): guided a junior
-- Designed reliable offset commit ordering: offsets committed only
+  engineer through initial implementation, then led a full refactor
-  after durable Spanner write, ensuring at-least-once delivery with
+  introducing hashed phone number lookup, removing non-indexed searches,
-  no data loss on crash
+  and tuning indexes — cutting CPU usage by ~30% under sustained load
-- Implemented retry cronjob requeuing up to 5 failed Spanner rows
+- Led Locust performance testing at 120 TPS steady and 600 TPS burst;
-  back to Kafka every 5 minutes with configurable backoff
+  used results to right-size GKE CPU and memory for stable production
-- Designed a zero-downtime interleaved index migration on a Cloud
+  behavior
-  Spanner accounts table under 400 TPS sustained read traffic
+- Designed OpenTelemetry + Datadog + Wiz observability stack; built CI
-- Designed OpenTelemetry integration with Datadog, defining trace,
+  controls with semantic version tag enforcement and least-privilege
-  span, and metrics strategy across services; integrated with Wiz
+  Workload Identity
-  for unified observability and security posture
+- Led TDD adoption, authored team dev guidelines, identified and
-- Built CI pipeline with semantic version tag enforcement — prevents
+  escalated a 1-month deadline slip, and stepped up as informal tech
-  image tag overwrites while allowing latest to update freely;
+  lead during a leadership gap
-  scoped Workload Identity permissions to read-only minimum
+- Applied AI tools (Copilot, Claude, Gemini, ChatGPT) in daily
-- Led performance testing with Locust (40 TPS steady / 120 TPS
+  workflows with deliberate guardrails: output validated through testing
-  burst); applied results to right-size GKE CPU/memory configs
+  and review, AI excluded from security-sensitive logic
-- Led TDD adoption for the team and authored development guidelines
-  covering milestone structure, ticket definition-of-done standards,
-  and code review expectations
-- Identified a 1-month deadline slip during mob programming,
-  escalated to leadership, facilitated full task breakdown and
-  schedule re-baseline across the team
-- Stepped up as informal tech lead during a leadership gap —
-  created progression guidelines, maintained ticket quality, and
-  kept formal leadership informed of all decisions and scope
-- Tasked with onboarding and upskilling Phase 2 application team
-  members to raise codebase quality ahead of next release
 
 
 ### 株式会社ニッポンダイナミックシステムズ — Tokyo
 **Full Stack Engineer, IT Solutions — Pharma Market Team**
 | Apr 2023 – Jul 2025
 
-- Built a scalable analytical DWH on Amazon Aurora (RDS) for a
+Backend, cloud infrastructure, data platforms, and internal application
-  pharmaceutical client, integrating Salesforce and multiple
+development for enterprise clients, primarily on AWS with some
-  external data sources via daily/weekly ETL batch pipelines using
+Azure-based delivery.
-  ECS/Fargate and Lambda; designed for HA with Multi-AZ failover
+
-- Constructed a SaaS data lake using AWS CDK + Glue +
+- Built a scalable analytical DWH on Amazon Aurora for a pharmaceutical
-  TypeScript/Python, fully automating ETL ingestion across
+  client, integrating Salesforce and multiple external sources via
-  heterogeneous data sources
+  ECS/Fargate and Lambda ETL pipelines; designed for HA with Multi-AZ
-- Developed an internal AI application using AWS Bedrock (Claude
+  failover
-  Sonnet) + React, implementing RAG-based document retrieval and
+- Constructed a SaaS data lake using AWS CDK, Glue, TypeScript, and
-  SES-based user matching in a small cross-functional team
+  Python, automating ETL ingestion across heterogeneous data sources
-- Built a license authentication service (Node.js + Docker + Azure
+- Built a license authentication service using Node.js, Docker, Azure
-  Web Apps + ADB2C), owning requirements definition, auth logic
+  Web Apps, and Azure AD B2C; owned requirements definition through
-  design, and client-facing communication
+  client delivery
-- Designed and automated monthly maintenance operations: AMI image
+- Automated monthly maintenance operations (AMI updates, patching,
-  updates, security patching, automated regression testing, and
+  regression testing, blue/green deployments) via AWS CodePipeline and
-  blue/green deployments via AWS CodePipeline and Azure Pipelines
+  Azure Pipelines
-- Conducted Docker image vulnerability scanning as part of CI/CD
+- Mentored junior engineers on cloud architecture; functioned as
-  pipeline; managed VPC, WAF, and Security Group configurations
+  bilingual (EN/JA) liaison between domestic and overseas engineering
-- Mentored junior engineers on cloud architecture patterns;
+  teams
-  functioned as bilingual (EN/JA) liaison between domestic and
-  overseas engineering teams
 
 
 ---
 
 ## SKILLS
 
-**Languages:** Go, Python, TypeScript/JavaScript
+| Category | Details |
-**Frameworks:** Gin, Flask, Next.js, Node.js
+|---|---|
-**Cloud — AWS:** ECS/Fargate, Lambda, Aurora/RDS, DynamoDB, Glue,
+| **Languages** | Go, Python, TypeScript/JavaScript, Java (learning; strong typed-language foundation) |
-  CDK, CodePipeline, Bedrock, Secrets Manager
+| **Backend** | Distributed systems, event-driven architecture, REST APIs, pub/sub, concurrency, retry design, idempotency, fault tolerance |
-**Cloud — GCP:** GKE, Cloud Spanner, Managed Kafka, BigQuery,
+| **Cloud — AWS** | ECS/Fargate, Lambda, Aurora/RDS, DynamoDB, Glue, CDK, CodePipeline, Bedrock, Secrets Manager |
-  Cloud Trace
+| **Cloud — GCP** | GKE, Cloud Spanner, Managed Kafka, BigQuery, Cloud Trace |
-**Cloud — Azure:** Web Apps, ADB2C, Azure Pipelines
+| **Cloud — Azure** | Web Apps, ADB2C, Azure Pipelines |
-**Data:** MySQL, Aurora, PostgreSQL, DynamoDB, Cloud Spanner,
+| **Data** | MySQL, Aurora, PostgreSQL, DynamoDB, Cloud Spanner, Kafka, Redis |
-  Kafka, Redis
+| **DevOps** | Docker, Kubernetes, ArgoCD, CI/CD, IaC (Terraform, AWS CDK, Ansible) |
-**DevOps:** Docker, Kubernetes, ArgoCD, CI/CD, IaC (AWS CDK,
+| **Observability** | OpenTelemetry, Datadog, distributed tracing |
-  Ansible)
+| **AI Tooling** | GitHub Copilot, ChatGPT, Gemini, Claude — applied with guardrails: test-validated output, excluded from security-critical paths |
-**Observability:** OpenTelemetry, Datadog, distributed tracing
+| **Security** | VPC, WAF, Security Groups, Secrets Manager, Workload Identity, Wiz |
-**AI Tooling:** GitHub Copilot (daily coding + code review),
-  Gemini (documentation + research), Claude (architecture
-  reasoning + coding), AWS Bedrock RAG (production)
-**Security:** VPC, WAF, Security Groups, Secrets Manager,
-  Workload Identity, Wiz, Docker vulnerability scanning
-**Other:** Homelab (k3s, self-hosted services, Ansible/IaC),
-  personal dev blog at nik4nao.com
 
 
 ---
@@ -146,12 +152,12 @@ Major: Electrical and Electronic Engineering
 Minor: Information Technology
 Graduated: March 2023
 
+
 ---
 
 ## ADDITIONAL
 
-- **Languages:** English (business), Japanese (JLPT N1), Malay (native)
+- **Languages:** English (business), Japanese (business, JLPT N1), Malay (native)
-- **Homelab:** Self-hosted k3s cluster, Gitea, Jellyfin, Cloudflare
+- **Homelab:** Self-hosted k3s cluster, Gitea, Ansible/IaC, ArgoCD —
-  Tunnel, Ansible-based IaC on Minisforum UM790 Pro
+  gitea.nik4nao.com (mirrored to github.com/nikafiq)
 - **Dev blog / personal site:** nik4nao.com
-- **Self-hosted Git:** gitea.nik4nao.com (mirrored to github.com/nikafiq)