Senior Data Platform Engineer (Integration) Singapore
Posted
Summary
Build global data ingestion capabilities (batch, streaming, API, file, CDC) for Momcozy's overseas data platform on Databricks/lakehouse, owning platform components end to end. Uses Python/Java, SQL, and Spark, with on-call support and cross-time-zone collaboration with China HQ; Singapore-based, no visa sponsorship.
About the Role
We are looking for a Senior Data Platform Engineer to build scalable data integration and external source connectivity capabilities. This role exists to build global data ingestion capabilities for our overseas data platform, which is being constructed from 0 to 1. You will design how to verify data is correctly ingested into the warehouse without seeing raw data content, due to compliance isolation. You will own platform components end to end and work with distributed teams to design, build, and operate data ingestion capabilities across batch, streaming, API, file, and CDC patterns.
Who You'll Work With Reports to: Head of Big Data & Algorithm (China HQ) Collaborates with: Data engineering teams across regions, product, engineering, and business teams; third-party data providers Team context: Works closely with Staff Data Platform Engineer and regional data teams; cross-time-zone collaboration with China HQ
Responsibilities Design, build, and operate scalable data platform capabilities, primarily on Databricks or comparable lakehouse platforms Own the end-to-end lifecycle of platform capabilities, from requirements and design through implementation, testing, deployment, and operations Build reusable platform components, automation, testing, and technical documentation Partner with distributed data, product, and engineering teams to translate business needs into actionable technical solutions Focus on batch, streaming, API, file, and CDC ingestion, including authentication, rate limits, incremental processing, schema evolution, and source reconciliation Participate in on-call support, incident response, and root-cause analysis Continuously improve platform reliability, security, performance, cost efficiency, and developer experience
Requirements Must-Have Bachelor's degree or above in Computer Science, Software Engineering, or a related field, or equivalent industry experience 5+ years of experience in data platform, data infrastructure, or backend engineering, or equivalent practical expertise Strong proficiency in Python / Java, SQL, and distributed data processing, with production experience using Spark or a comparable engine Experience with cloud data platforms, lakehouse architecture, orchestration, CI/CD, and production observability Ability to independently design, build, test, deploy, and troubleshoot platform components in production Legally authorized to work in Singapore; this role does not provide visa sponsorship Nice-to-Have Experience with Databricks, Kafka, Airflow, dbt, or comparable technologies Experience integrating third-party SaaS, advertising, commerce, or consumer platforms Experience with web data collection, RPA, or multimodal data ingestion Mandarin communication skills
Language Professional working proficiency in English (CEFR B2 or above) Mandarin Chinese is highly advantageous for collaboration with China HQ, but not required
What We Offer Opportunity to build core data integration capabilities for a global platform Hands-on engineering with modern lakehouse technologies Cross-regional collaboration with distributed data teams Competitive compensation and benefits package Flexible working policy
Who You'll Work With Reports to: Head of Big Data & Algorithm (China HQ) Collaborates with: Data engineering teams across regions, product, engineering, and business teams; third-party data providers Team context: Works closely with Staff Data Platform Engineer and regional data teams; cross-time-zone collaboration with China HQ
Responsibilities Design, build, and operate scalable data platform capabilities, primarily on Databricks or comparable lakehouse platforms Own the end-to-end lifecycle of platform capabilities, from requirements and design through implementation, testing, deployment, and operations Build reusable platform components, automation, testing, and technical documentation Partner with distributed data, product, and engineering teams to translate business needs into actionable technical solutions Focus on batch, streaming, API, file, and CDC ingestion, including authentication, rate limits, incremental processing, schema evolution, and source reconciliation Participate in on-call support, incident response, and root-cause analysis Continuously improve platform reliability, security, performance, cost efficiency, and developer experience
Requirements Must-Have Bachelor's degree or above in Computer Science, Software Engineering, or a related field, or equivalent industry experience 5+ years of experience in data platform, data infrastructure, or backend engineering, or equivalent practical expertise Strong proficiency in Python / Java, SQL, and distributed data processing, with production experience using Spark or a comparable engine Experience with cloud data platforms, lakehouse architecture, orchestration, CI/CD, and production observability Ability to independently design, build, test, deploy, and troubleshoot platform components in production Legally authorized to work in Singapore; this role does not provide visa sponsorship Nice-to-Have Experience with Databricks, Kafka, Airflow, dbt, or comparable technologies Experience integrating third-party SaaS, advertising, commerce, or consumer platforms Experience with web data collection, RPA, or multimodal data ingestion Mandarin communication skills
Language Professional working proficiency in English (CEFR B2 or above) Mandarin Chinese is highly advantageous for collaboration with China HQ, but not required
What We Offer Opportunity to build core data integration capabilities for a global platform Hands-on engineering with modern lakehouse technologies Cross-regional collaboration with distributed data teams Competitive compensation and benefits package Flexible working policy