Data Platform Engineer

Tap Growth ai; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Tap Growth ai is recruiting a Data Platform Engineer to design, build, and optimize modern analytics platforms and lakehouse solutions. You will develop scalable data pipelines and optimize distributed query workloads across a high-performance data ecosystem.

The role requires deep expertise in data architectures, MPP platforms, and large-scale analytics processing, with collaboration across architects, analysts and engineers to ensure reliable and scalable data solutions.

Qualifications

• Bachelor's degree in CS/IT/Data Engineering or related field.
• 7-8+ years in Data Engineering, Analytics Engineering, or Big Data ecosystems.
• Experience in enterprise-scale analytics environments.
• Strong analytical, problem solving and stakeholder management skills.

Responsibilities

• Design, develop and optimize enterprise data platforms and analytics solutions.
• Build scalable data pipelines and lakehouse architectures.
• Support and optimize MPP query engines, data warehouses and distributed environments.
• Drive performance tuning, platform modernization and workload optimization.
• Collaborate with architects, analysts and engineering teams to deliver scalable data solutions.
• Support platform automation, CI/CD, governance and operational best practices.
• Troubleshoot complex data platform issues and ensure operational excellence.

Skills

Analytical thinking

Problem solving

Stakeholder management

Communication

Education

Bachelor's Degree in Computer Science, Information Technology, Data Engineering, or a related discipline

Tools

Apache Doris

StarRocks

ClickHouse

Greenplum

Iceberg

Delta Lake

Apache Hudi

Snowflake

Apache Spark

Trino/PrestoSQL

Presto

Parquet

ORC

Python

Java

Scala

Git

CI/CD pipelines

Job description

We're Hiring: Data Platform Engineer!

We are seeking an experienced Data Platform Engineer to design, build, optimize, and support modern analytics platforms and lakehouse solutions. You will play a key role in developing scalable data pipelines, optimizing distributed query workloads, and supporting enterprise analytics platforms across a high-performance data ecosystem. Candidates should possess deep expertise in modern data architectures, MPP platforms, and large-scale analytical processing.

Key Responsibilities

• Design, develop, and optimize enterprise data platforms and analytics solutions.
• Build and maintain scalable data pipelines and lakehouse architectures.
• Support and optimize MPP query engines, data warehouses, and distributed processing environments.
• Drive performance tuning, platform modernization, and workload optimization initiatives.
• Collaborate with architects, analysts, and engineering teams to deliver reliable and scalable data solutions.
• Support platform automation, CI/CD, governance, and operational best practices.
• Troubleshoot complex data platform issues and ensure operational excellence.

General Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Data Engineering, or a related discipline.
• 7-8+ years of experience in Data Engineering, Analytics Engineering, Data Platforms, or Big Data ecosystems.
• Experience working in enterprise-scale analytics and data environments.
• Strong analytical, problem-solving, and stakeholder management skills.

Mandatory Skills

• Hands-on experience with Apache Doris (or similar MPP platforms such as StarRocks, ClickHouse, or Greenplum).
• Advanced SQL development and query optimization skills.
• Strong understanding of Apache Doris architecture, data models, partitioning, and performance tuning.
• Experience with Apache Iceberg, Delta Lake, or Apache Hudi.
• Experience with Snowflake and/or Apache Spark.
• Hands-on experience with Trino, PrestoSQL, or Presto.
• Solid knowledge of MPP/distributed query processing, performance optimization, and data architecture concepts.
• Experience working with cloud object storage, Parquet, and ORC file formats.
• Proficiency in Python, Java, or Scala.
• Experience with Git and CI/CD pipelines for data platforms.