Jul 2024 – Present · 1 yr 11 mos · Singapore · Hybrid

• Engineering Manager & Data Architect with 13+ years of experience designing and scaling cloud-native, high-throughput data platforms that power analytics, machine learning, and business-critical decision-making.
• At Autodesk, I lead and mentor a team of data engineers building real-time and batch processing systems using Apache Flink, Spark, Kafka, and Snowflake across AWS. I own end-to-end data architecture—from ingestion and stream processing to governance and performance optimization—supporting large-scale, multi-tenant data workloads.
• Key Data Platform Use Cases
• Enterprise Streaming Data Platform: Architected and built a real-time streaming platform that ingests and processes data from all Autodesk products, handling ~400K events per second with sub-100 ms end-to-end data availability, enabling near real-time analytics and downstream ML workloads.
• Customer Journey Analytics Pipeline: Designed a high-throughput pipeline to process customer journey and behavioral data at ~300K events per second, consistently achieving ~100 ms latency, empowering product teams with real-time insights into user behavior and engagement.
• I specialize in:
• Designing scalable, fault-tolerant streaming and batch architectures
• Driving data platform modernization and cloud adoption
• Improving system reliability, performance, and cost efficiency
• Translating business requirements into technical strategy
• Leading cross-functional initiatives across Product, ML, and Analytics teams
• With a strong foundation in backend engineering (Java, Python, SQL) and a systems-thinking mindset, I enjoy solving complex data challenges while balancing engineering excellence, security, and operational simplicity.
• I’m passionate about technical leadership, mentorship, and building high-performing teams that deliver impactful data products. Always open to connecting with data engineering leaders, architects, and engineers working on large-scale streaming system.

Apr 2018 – Jun 2024 · 6 yrs 2 mos · Singapore · Hybrid

• Lead a team of 6 data engineers in architecting, developing, and maintaining scalable, high-throughput data pipelines that align with strategic business goals.
• Partner with data scientists, analysts, and software engineers to gather requirements and deliver robust, production-ready data solutions.
• Design and implement real-time streaming and batch ETL pipelines, enabling ingestion, transformation, and storage of large-scale datasets into a centralized data lake.
• Establish data quality frameworks and monitoring systems to ensure accuracy, consistency, and reliability across pipelines.
• Provide technical leadership and mentorship, fostering a culture of innovation, knowledge sharing, and continuous improvement.
• Proficient in Java, Python, SQL, with a strong command of distributed data processing.
• Hands-on expertise with big data technologies: Apache Flink, Spark, Kafka, Hive.
• Skilled in backend system design using Spring Boot, RESTful APIs, Microservices architecture, and relational/non-relational databases (MySQL, PostgreSQL, MongoDB).
• Experienced in deploying data infrastructure on AWS and Google Cloud Platform, leveraging services for compute, storage, and orchestration.
• Familiar with modern DevOps and containerization tools: Apache Airflow, Docker, Jenkins, Spinnaker.