Senior Data Engineer — Pipelines & Architecture (Singapore)

Tap Growth ai; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Tap Growth ai is seeking an experienced Data Engineer to design, build, and maintain robust data pipelines and architectures in Singapore. The role emphasizes data availability, quality, and security across the organization and demands strong collaboration with analytics teams.

The candidate should have at least 8 years of hands-on data engineering experience, including batch and real‑time processing, and with cloud services like Azure Data Factory, Databricks, Snowflake, or Kafka.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, or related field.
• At least 8 years’ working experience in data platform, data analytics or relevant projects.
• Proven experience as a Data Engineer, with design and managing enterprise data architecture.
• Experience with batch and real time processing.
• Strong programming in Python, SQL, SAS, or R for data engineering tasks.
• Experience with data processing tools (Informatica, Kettle, Talend, Airflow, Dolphin).
• Experience with cloud platforms (Azure Data Factory, Databricks, Snowflake, Kafka).
• Experience with data storage (SQL/NoSQL, Vector and Graph).
• BI tool experience (Power BI, Tableau).
• Excellent problem-solving and ability to work with large data sets.
• Strong communication with non-technical stakeholders.

Skills

Problem-solving

Attention to detail

Communication

Independence

Team collaboration

AI tech stack

BI tools exposure

Education

Bachelor's degree in CS/Data Science/Statistics or related

Tools

Python

SQL

SAS

R

Job description

Tap Growth ai is seeking an experienced Data Engineer to design, build, and maintain robust data pipelines and architectures in Singapore. The role emphasizes data availability, quality, and security across the organization and demands strong collaboration with analytics teams.

The candidate should have at least 8 years of hands-on data engineering experience, including batch and real‑time processing, and with cloud services like Azure Data Factory, Databricks, Snowflake, or Kafka.