Daniel is available for hire
Hire DanielDaniel Kurniadi
Verified Expert in Engineering
Site Reliability Engineer and Developer
Singapore, Singapore
Toptal member since June 19, 2026
Bio
Daniel is a senior site reliability engineer with over 5 years of experience in cloud infrastructure and automation for clients including Thought Machine, Arta Finance, and TikTok Inc. His primary expertise is in Kubernetes, Terraform, and AWS for fintech and data platforms, where he thrives in high-scale, regulated environments. He cut legacy cloud infrastructure costs by $320,000 annually for a banking-tech client.
Portfolio
Freelance Clients
Linux, TypeScript, Python, Docker, Terraform, Ansible...
Thought Machine
Google Cloud Platform (GCP), Terraform, Kubernetes, Linux, Python, Ansible...
Arta
PostgresQL, Apache Airflow, Google Cloud Platform (GCP), Kubernetes...
Experience
- DevOps - 6 years
- Terraform - 6 years
- Kubernetes - 6 years
- Linux - 6 years
- Amazon Web Services (AWS) - 6 years
- Continuous Delivery (CD) - 6 years
- Hybrid Cloud Infrastructure - 6 years
- Google Cloud Platform (GCP) - 4 years
Preferred Environment
Kubernetes, Docker, Ansible, Terraform, Google Cloud Platform (GCP)
The most amazing...
...platform I've built is a centralized observability system that cut legacy costs by $320,000 and unified incident context across teams.
Work Experience
DevOps Engineer
2025 - 2026
Freelance Clients
- Consolidated 6 disconnected web applications (2 corporate portals, 2 eCommerce storefronts, and 2 automated transaction renewal portals) onto an optimized AWS ECS deployments architecture behind load balancers (ALB) and AWS WAF.
- Rearchitected multi-app routing configurations combining a legacy WordPress engine and a modern PHP/Laravel transaction application, streamlining automated sync using background processes.
- Hardened overall application security posture to mitigate active runtime distributed/brute-force login attacks.
- Integrated AWS WAF rulesets and forced strict IP-whitelisting on administrative back ends.
- Developed an optimized responsive web application using a modern tech stack (React, Tailwind, Netlify) and CMS server, allowing seamless toggling between three user portals in one app: learners, trainers, and enterprises.
Technologies: Linux, TypeScript, Python, Docker, Terraform, Ansible, Google Cloud Platform (GCP)
Senior Site Reliability Engineer, Banking Platform
2024 - 2025
Thought Machine
- Architected the infrastructure for managed card-data environment in AWS Cloud Network that enabled our Tier-1 banking partner to launch their debit card product and ensuring full regulatory ISO20020 and PCI-DSS compliance.
- Led development of Terraform libraries for a multi-cloud (AWS/GCP) setup and implemented a Terraform CD pipeline with premerge Terraform plan, automated Terratest validations, and OPA policy enforcement.
- Spearheaded a centralized Prometheus/Thanos observability platform with self-serve Grafana dashboards, accelerating mean-time-to-detection (MTTD) by 40% and cutting legacy cloud costs by $320,000 annually.
- Engineered a cloud-agnostic Kubernetes operator to fully automate the provisioning, management, and configuration of Kafka clusters.
- Reduced the time-to-deploy to a production system from days to under an hour and ensured high availability through automated fail-over testing for multi-AZ and regional failures.
- Streamlined series of database operations with automated pipeline for Schema migrations, Postgres upgrade, and AWS RDS-to-Aurora migration that saved 12+ engineering hours per week from manual DBA operations across 70+ fleets.
Technologies: Google Cloud Platform (GCP), Terraform, Kubernetes, Linux, Python, Ansible, Continuous Delivery (CD)
Senior Cloud Platform Engineer, Core Trading
2022 - 2024
Arta
- Provisioned production-grade GKE clusters to support high-frequency trading and ledger systems.
- Designed fault-tolerant async workflows using Temporal.io to manage stateful order aggregation and KYC status updates, achieving a 99.1% month-over-month success rate.
- Engineered comprehensive users KYC workflow that became the primary gateway for capital inflow and facilitated the onboarding of $5+ million (on average) new monthly AUM by converting 100+ high-net-worth leads into funded accounts.
- Delivered a real-time data and batch processing analytics platform that processes and stores data on asset information, CUSIPs, stock prices, equity curves, and risk factor model matrices that powered our user-facing application dashboard.
Technologies: PostgresQL, Apache Airflow, Google Cloud Platform (GCP), Kubernetes, Google Kubernetes Engine (GKE), Pulumi, Jenkins Pipeline, GitHub Actions, GitHub Workflows
Software Engineer, ByteHouse Data Platform
2020 - 2022
TikTok
- Architected a high-performance back end routing ByteHouse SQL queries. Optimized memory buffers to reach a 455 MBs data transfer rate.
- Implemented a feature-rich SQL editor using React.js and CodeMirror, incorporating real-time syntax highlighting, schema-aware auto-completion, and error feedback to streamline query execution at petabyte scale.
- Developed asynchronous job orchestration for petabyte-scale data transfer from Kafka, S3, and Hive into ByteHouse storage, delivering 200+ jobs per day of data ingestions, which total to 230 GB of data a day (peak).
- Delivered a Kubernetes operator that manages the end-to-end lifecycle of the distributed warehouse clusters and automates version upgrades and installation steps, as well as enabling automatic hibernation.
Technologies: Kubernetes, PostgresQL, Apache Spark, Apache Hive, Apache Kafka, Amazon Web Services (AWS)
Machine Learning Engineer (Intern)
2020 - 2020
Gojek
- Trained object detection models for pedestrian scenes and deployed trained models to an LCD screen device using ONNX and Torchscript.
- Benchmarked off-the-shelf models like Retina Net and Yolov2 Net, and employed Kalman filtering to track detected objects once bounding boxes are generated.
- Developed and managed the release of the Merlin Python3 SDK for our engineers, where this SDK enables the deployment of machine learning instances to staging and production clusters in GCP.
Technologies: Python, C++, Linux, Kubernetes, Google Cloud Platform (GCP)
Software Engineer, Zendesk Chat Testing Automation Team
2019 - 2019
Zendesk
- Orchestrated Jenkins pipeline for end-to-end testing in staging and production pods.
- Developed and maintained end-to-end automation testing platform services and testing frameworks based on Selenium that include APIs and UI testing.
- Delivered continuous integrations in the QA stage with SauceLabs, where regression test recording can be captured and sent for review and debugging.
- Integrated UI event tracking and monitoring to allow insights about user interactivity, feature usage, and UX usability.
Technologies: Jenkins Pipeline, Java SE (Core Java)
Experience
Professional Development Portfolio and Blog Posts
A portfolio about real-world projects across different industries, heavily utilizing AWS, GCP, and modern cloud and big data stacks. Because much of a DevOps and solutions architect's work is confidential and highly complex, aspiring software architects often struggle to build portfolios. Hence, we built this website to inspire others and serve as a reference.
Education
2016 - 2020
Bachelor's Degree in Electrical Engineering
Nanyang Technological University - Singapore
Skills
Libraries/APIs
Jenkins Pipeline
Tools
Terraform, Google Kubernetes Engine (GKE), Apache Airflow, Jenkins, Ansible
Languages
Python, TypeScript, C++, JavaScript, Java SE (Core Java)
Paradigms
Continuous Delivery (CD), DevOps
Platforms
Linux, Google Cloud Platform (GCP), Kubernetes, Amazon Web Services (AWS), Apache Kafka, Docker
Frameworks
Apache Spark
Storage
Apache Hive, MySQL
Other
AWS Cloud Security, Hybrid Cloud Infrastructure, PostgresQL, Electrical Engineering, Pulumi, GitHub Actions, GitHub Workflows, Software System Architecture Development
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