Senior Big Data Engineering Manager

Unison Consulting; Singapore; On-site; SGD 89,000 - 112,000; Full time

Job summary

Unison Consulting is seeking an experienced Data Engineering Manager in Singapore to lead enterprise data architecture and Big Data platform initiatives. You will guide cross-functional teams, tackle complex data challenges, and drive scalable ETL/ELT pipelines for critical financial systems.

The role requires deep Python, PySpark, and SQL expertise, plus hands-on leadership across enterprise data platforms. On-site position with strong growth prospects and banking domain focus.

Qualifications

• Minimum 10+ years of progressive professional experience in data engineering, Big Data development, and enterprise data platforms.
• Strong hands-on expertise in Big Data technologies, Python, PySpark, SQL, and distributed data processing frameworks.
• Experience leading data engineering teams, managing deliverables, and driving technical execution.
• Experience designing and managing complex data pipelines, ETL/ELT workflows, and scalable data platforms.
• Ability to lead跨-functional teams across banking/financial services domains and engage executive stakeholders.

Responsibilities

• Lead enterprise-level data engineering initiatives and Big Data platform development.
• Provide hands-on technical guidance and troubleshooting for complex data architectures.
• Design, build, optimize, and maintain complex data pipelines and workflows.
• Establish data modeling, architecture standards, and performance optimization practices.
• Mentor the data engineering team and drive sprint planning in Agile environments.

Skills

Big Data

Python

PySpark

SQL

Team leadership

ETL/ELT

Education

Bachelor's or Master’s degree in CS/Engineering

Tools

Databricks

AWS

Azure

GCP

Airflow

Kubernetes

Job description

Unison Consulting is seeking an experienced Data Engineering Manager in Singapore to lead enterprise data architecture and Big Data platform initiatives. You will guide cross-functional teams, tackle complex data challenges, and drive scalable ETL/ELT pipelines for critical financial systems.

The role requires deep Python, PySpark, and SQL expertise, plus hands-on leadership across enterprise data platforms. On-site position with strong growth prospects and banking domain focus.