Data Engineer

ETHOZ Capital Ltd; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

ETHOZ Capital Ltd is seeking a data engineer to design, build, and maintain scalable data pipelines and architectures in Singapore.

You will collaborate with data scientists and analysts to enable analytics, ML, and BI use cases, while ensuring data quality, governance, and cost efficiency.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline.
• Minimum 3 years of relevant experience in data engineering or related roles.
• Relevant professional certifications (cloud, data, or analytics) are an advantage.
• Strong proficiency in SQL and at least one programming language such as Python, Java, or Scala.
• Experience with data pipeline and workflow orchestration tools (e.g. Airflow, Prefect, PowerBI or equivalent).
• Hands-on experience with data warehousing technologies (e.g. Snowflake, BigQuery, Redshift, or similar).
• Familiarity with cloud platforms (AWS, Azure, or GCP), including data storage and processing services.
• Experience working with structured and unstructured data.
• Understanding of data modelling, schema design, and performance optimisation.
• Knowledge of data security, access control, and governance best practices.

Responsibilities

• Design, develop, and maintain robust, scalable data pipelines and ETL/ELT processes.
• Build and manage data architectures including data lakes, data warehouses, and real-time streaming systems.
• Integrate data from multiple internal and external sources, ensuring data accuracy, consistency, and timeliness.
• Collaborate with data scientists, analysts, and software engineers to support analytics, machine learning, and business intelligence use cases.
• Optimise data storage, processing performance, and cost efficiency.
• Implement data quality checks, monitoring, and documentation.
• Ensure data governance, security, and compliance with PDPA and internal data policies.
• Troubleshoot data issues and provide ongoing operational support.
• Participate in system design reviews, technical documentation, and knowledge sharing.

Skills

SQL

Python

Java

Scala

Airflow

Prefect

Data modeling

Data governance

Data warehousing

Education

Bachelor Degree in Computer Science, Information Systems, Engineering, or a related discipline

Tools

Airflow

Prefect

Power BI

Snowflake

BigQuery

Redshift

AWS

Azure

GCP

Job description

Key Responsibilities

• Design, develop, and maintain robust, scalable data pipelines and ETL/ELT processes

• Build and manage data architectures including data lakes, data warehouses, and real-time streaming systems

• Integrate data from multiple internal and external sources, ensuring data accuracy, consistency, and timeliness

• Collaborate with data scientists, analysts, and software engineers to support analytics, machine learning, and business intelligence use cases

• Optimise data storage, processing performance, and cost efficiency

• Implement data quality checks, monitoring, and documentation

• Ensure data governance, security, and compliance with PDPA and internal data policies

• Troubleshoot data issues and provide ongoing operational support

• Participate in system design reviews, technical documentation, and knowledge sharing

Requirements and Competencies:

• Bachelor Degree in Computer Science, Information Systems, Engineering, or a related discipline

• Minimum 3 years of relevant experience in data engineering or related roles

• Relevant professional certifications (cloud, data, or analytics) are an advantage

• Strong proficiency in SQL and at least one programming language such as Python, Java, or Scala

• Experience with data pipeline and workflow orchestration tools (e.g. Airflow, Prefect, PowerBI or equivalent)

• Hands-on experience with data warehousing technologies (e.g. Snowflake, BigQuery, Redshift, or similar)

• Familiarity with cloud platforms (AWS, Azure, or GCP), including data storage and processing services

• Experience working with structured and unstructured data

• Understanding of data modelling, schema design, and performance optimisation

• Knowledge of data security, access control, and governance best practices