Data Engineer (Pyspark,Python,SQL,ETL)

Unison Group; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Unison Group in Singapore is seeking a Data Engineer with hands-on Python, PySpark and SQL to design, develop, and maintain scalable data pipelines that support enterprise analytics and reporting. The role emphasizes data transformation (ETL/ELT), data quality, and working with large datasets on modern data platforms.

The ideal candidate will collaborate with business analysts, data architects, and data scientists to implement scalable data solutions and optimize performance across pipelines and

Qualifications

• Proficiency in Python, SQL and PySpark for ETL pipelines.
• Experience in ETL/ELT processes and data transformation.
• Ability to participate in code reviews and production support.
• Knowledge of data governance, security, and regulatory standards.
• Experience with data modelling and data quality checks.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Python, PySpark, and SQL.
• Perform data extraction, transformation, and loading from multiple source systems into enterprise data platforms.
• Develop reusable data transformation logic to support business reporting, analytics, and machine learning initiatives.
• Optimize SQL queries and PySpark jobs to improve performance and processing efficiency.
• Build and maintain data models, staging layers, and curated datasets for downstream consumption.
• Perform data cleansing, validation, reconciliation, and quality checks to ensure data accuracy and consistency.
• Troubleshoot and resolve data pipeline failures, performance bottlenecks, and data-related issues.
• Collaborate with business analysts, data architects, and data scientists to understand data requirements and implement scalable solutions.

Skills

Python

SQL

ETL

Tools

PySpark

Job description

ROLE OVERVIEW

We are seeking a skilled Data Engineer with hands‑on experience in Python, PySpark, and SQL to design, develop, and maintain scalable data pipelines that support enterprise analytics and reporting. The ideal candidate will have strong experience in data transformation (ETL/ELT), data quality, and working with large datasets in modern data platforms.

KEY RESPONSIBILITIES

• Design, develop, and maintain scalable ETL/ELT pipelines using Python, PySpark, and SQL
• Perform data extraction, transformation, and loading from multiple source systems into enterprise data platforms
• Develop reusable data transformation logic to support business reporting, analytics, and machine learning initiatives
• Optimize SQL queries and PySpark jobs to improve performance and processing efficiency
• Build and maintain data models, staging layers, and curated datasets for downstream consumption
• Perform data cleansing, validation, reconciliation, and quality checks to ensure data accuracy and consistency
• Troubleshoot and resolve data pipeline failures, performance bottlenecks, and data-related issues
• Collaborate with business analysts, data architects, and data scientists to understand data requirements and implement scalable solutions

REQUIREMENTS

• Skills required -Python, SQL, Pyspark, ETL
• Participate in code reviews, testing, deployment, and production support activities
• Develop and maintain technical documentation, including data mappings, transformation logic, and ETL workflows
• Ensure compliance with data governance, security, and regulatory standards
• Monitor scheduled ETL jobs and proactively address operational issues