Senior Data Engineer: AI-Driven Data Platform

PVH (Tommy Hilfiger/Calvin Klein); Singapore; Hybrid; SGD 90,000 - 140,000; Full time

Job summary

Goodnotes is building an AI-native data platform to empower engineers and product teams with reliable analytics at scale. As a Senior Data Engineer on the Data Platform team, you will design pipelines, models, and systems powering analytics, experimentation, and AI-driven product decisions.

You'll work with Analytics Engineers, Data Scientists, and Product Engineers to create a scalable, observable, and self-serve data platform, leveraging Snowflake, dbt, Iceberg, Kafka, and AWS in a hybrid

Qualifications

• Significant experience as a Data Engineer building production-grade data platforms.
• Strong SQL skills and data modeling experience.
• Experience with cloud-native data platforms on AWS.
• Experience with batch and streaming data infrastructures (Kafka, Confluent, Pulsar).
• Knowledge of data quality, testing, monitoring, observability, and operational excellence.
• Excellent collaboration across engineering, product, and data teams.
• Familiarity with dbt, Snowflake, ClickHouse, Iceberg is a plus.

Responsibilities

• Design and build reliable data pipelines powering analytics and AI features.
• Shape the data platform architecture and tooling.
• Collaborate with engineers, data scientists, and product teams.
• Improve engineering productivity and data platform operability.
• Ensure data quality, lineage, and observability.

Skills

SQL proficiency

Data pipelines

Cloud AWS

Real-time streaming

Observability

Cross-functional

Ownership

Tools

Snowflake

dbt

Apache Iceberg

ClickHouse

Kafka

Confluent

Pulsar

AWS

Job description

Goodnotes is building an AI-native data platform to empower engineers and product teams with reliable analytics at scale. As a Senior Data Engineer on the Data Platform team, you will design pipelines, models, and systems powering analytics, experimentation, and AI-driven product decisions.

You'll work with Analytics Engineers, Data Scientists, and Product Engineers to create a scalable, observable, and self-serve data platform, leveraging Snowflake, dbt, Iceberg, Kafka, and AWS in a hybrid