Data Engineering Manager - Big Data

Hong Kong Unison Limited; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Hong Kong Unison Limited in Singapore seeks a technically strong Data Engineering Manager to lead enterprise data platforms and scalable pipelines, guiding teams, delivering robust ETL/ELT workflows, and ensuring production-ready code.

The ideal candidate has 10+ years in data engineering, hands-on Big Data tech (Hadoop, Spark, PySpark, Hive, Kafka), strong Python/SQL skills, and proven leadership across cloud platforms (AWS/Azure/GCP) with data governance and delivery focus.

Qualifications

• 10+ years of data engineering and enterprise data platform experience.
• Hands-on expertise with Big Data technologies and guiding teams.
• Proficiency in Python, PySpark, SQL, and distributed processing.
• Experience building and managing complex data pipelines and ETL/ELT workflows.
• Proven track record leading data engineering teams and delivering solutions.
• Strong data modeling, architecture, performance optimization, and scalability skills.
• Experience with cloud-based data platforms is highly desirable.
• Excellent stakeholder management and leadership abilities.

Responsibilities

• Lead and manage data engineering teams to design, develop, and deliver scalable enterprise data platforms and pipelines.
• Maintain hands-on expertise in Big Data technologies such as Hadoop, Spark, PySpark, Hive, Kafka.
• Design and implement robust ETL/ELT pipelines, data ingestion frameworks, data transformation, and data integration solutions.
• Drive data engineering architecture, design, performance tuning, and optimization of large-scale data processing workloads.
• Manage data lake, data warehouse, and modern cloud-based data platform implementations.
• Work with cloud platforms such as AWS, Azure, or GCP and technologies such as Databricks, where applicable.
• Lead data quality, data governance, metadata management, security, and data reliability initiatives.
• Collaborate with solution architects, data architects, business stakeholders, and project managers to translate business requirements into technical solutions.
• Manage project delivery, resource allocation, technical reviews, risk mitigation, and delivery timelines.
• Mentor engineers, establish engineering best practices, and ensure high-quality, maintainable, and production-ready code.

Skills

Data engineering

Big Data

Python

PySpark

SQL

Data pipelines

Leadership

Cloud data platforms

Stakeholder management

Data modeling

Tools

Hadoop

Spark

Hive

Kafka

Databricks

AWS

Azure

GCP

Job description

Location: Singapore
Experience: 10+ years in Data Engineering, including hands-on Big Data expertise and team management
Domain: Banking / Financial Services preferred

Key Responsibilities

• Lead and manage data engineering teams to design, develop, and deliver scalable enterprise data platforms and pipelines.
• Maintain strong hands-on expertise in Big Data technologies such as Hadoop, Spark, PySpark, Hive, Kafka, and distributed data processing.
• Design and implement robust ETL/ELT pipelines, data ingestion frameworks, data transformation, and data integration solutions.
• Drive data engineering architecture, technical design, performance tuning, and optimization of large-scale data processing workloads.
• Manage data lake, data warehouse, and modern cloud-based data platform implementations.
• Work with cloud platforms such as AWS, Azure, or GCP and technologies such as Databricks, where applicable.
• Lead data quality, data governance, metadata management, security, and data reliability initiatives.
• Collaborate with solution architects, data architects, business stakeholders, and project managers to translate business requirements into technical solutions.
• Manage project delivery, resource allocation, technical reviews, risk mitigation, and delivery timelines.
• Mentor engineers, establish engineering best practices, and ensure high-quality, maintainable, and production-ready code.

Required Skills and Experience

• 10+ years of experience in data engineering, Big Data development, and enterprise data platforms.
• Proven hands-on experience in Big Data technologies, with the ability to guide teams technically and troubleshoot complex engineering challenges.
• Strong proficiency in Python, PySpark, SQL, and distributed data processing frameworks.
• Experience building and managing complex data pipelines, ETL/ELT workflows, and large-scale data processing solutions.
• Demonstrated experience leading data engineering teams, managing deliverables, and driving technical execution.
• Strong understanding of data modelling, data architecture, performance optimization, and data platform scalability.
• Experience with cloud-based data engineering and modern data platforms is highly desirable.
• Excellent stakeholder management, communication, problem-solving, and leadership skills.

Preferred

Preferred: Experience in banking, financial services, regulatory reporting, risk analytics, or other data-intensive enterprise environments.

Ideal Candidate

A technically strong Data Engineering Manager who combines practical Big Data development experience with proven people leadership, solution delivery, and the ability to guide engineers through complex data engineering challenges.