Data Engineer – Leading Financial Institution

PFCC Group; Hong Kong; On-site; HKD 420,000 - 720,000; Full time

Job summary

PFCC Group is seeking a Data Engineer to join its Data Services team in Hong Kong. You will design, build, maintain, and optimise data lakes, pipelines and processing systems that support analytics and operations.

The role requires strong Python and AWS/cloud experience, with collaboration across data scientists, product teams and engineers. Independent, hands-on work and clear communication are essential for delivering end-to-end data solutions.

Qualifications

• Bachelor’s degree in CS/IT/Engineering or related field.
• Hands-on data engineering experience with Python and Spark/PySpark.
• Experience with AWS cloud services and data orchestration tools like Airflow.
• Familiarity with Redshift, Athena, Hive/Hadoop and Docker/Kubernetes is advantageous.

Responsibilities

• Design, build, maintain and optimise data lakes, databases, data pipelines and batch/real-time processing systems.
• Collaborate with data science and product teams to integrate data sources and develop scalable data models.
• Work with AWS and big data tools to deliver reliable, scalable data solutions.
• Support workflow orchestration, testing, CI/CD, version control, monitoring and troubleshooting.

Skills

Analytical thinking

Communication skills

Independent work

Education

Bachelor’s degree in Computer Science / Information Technology / Engineering

Tools

Python

PySpark

Spark

AWS

S3

Glue

EMR

EC2

Lambda

Airflow

Redshift

Athena

Hive/Hadoop

Kafka

Docker/Kubernetes

CI/CD

Git

Job description

Our client, a leading digital financial institution, is seeking a Data Engineer to join its Data Services team. This role focuses on designing, maintaining, and improving data platforms and infrastructure that support critical analytical and operational functions across the organisation.

We are looking for a logical, adaptable, and hands-on Data Engineer with strong Python and cloud/data engineering experience, who is comfortable working independently and collaborating with data scientists, product teams, and other engineers.

Key Responsibilities:

• Data Platform & Pipeline Development: Design, build, maintain, and optimise data lakes, databases, data pipelines, and batch/real-time processing systems.
• Data Integration & Modelling: Collaborate with data science and product teams to integrate new data sources, structure data schemas, and develop scalable data models.
• Cloud & Big Data Engineering: Work with AWS and big data technologies to deliver reliable, scalable, and high-performing data solutions.
• Monitoring & Engineering Best Practices: Support workflow orchestration, testing, CI/CD, version control, monitoring, documentation, and troubleshooting across data environments.

Qualifications and Requirements:

• Bachelor’s Degree in Computer Science, Information Technology, Engineering, or a related discipline.
• Proven experience in Data Engineering, Software Engineering, or a related technical role.
• Strong hands‑on experience with Python and data processing technologies such as PySpark/Spark.
• Experience with AWS cloud services, particularly S3, Glue, EMR, EC2, Lambda, or similar.
• Familiarity with data orchestration tools such as Apache Airflow, and databases such as Redshift, Athena, or Hive/Hadoop.
• Exposure to Kafka, Docker/Kubernetes, CI/CD, and Git is highly advantageous.
• Strong analytical and problem‑solving skills, with the ability to work independently and deliver projects end‑to‑end.
• Excellent communication and collaboration skills, with good command of English.
• Experience in banking, financial services, or fintech is an advantage.