Data Engineer – Leading Financial Institution

PFCC Group; Hong Kong; On-site; HKD 600,000 - 900,000; Full time

Job summary

PFCC Group, a leading digital financial institution, is seeking a Data Engineer to join its Data Services team in Hong Kong. Design, build, and optimise data lakes, pipelines, and processing systems to support analytics and operations.

Strong Python and cloud/data engineering experience required, with autonomous and collaborative work style. You will work with AWS services (S3, Glue, EMR, Lambda), Spark, Airflow, and databases such as Redshift/Athena.

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering or related discipline.
• Proven experience in Data Engineering or Software Engineering.
• Strong hands-on Python and data processing with PySpark/Spark.
• Experience with AWS cloud services (S3, Glue, EMR, EC2, Lambda).
• Familiarity with data orchestration (Airflow) and databases (Redshift/Athena/Hive).
• Exposure to Kafka, Docker/Kubernetes, CI/CD, and Git is advantageous.
• Excellent analytical, problem-solving, and communication skills.
• Experience in banking/fintech is an advantage.

Responsibilities

• Design, build, and maintain data lakes, databases, and pipelines.
• Collaborate with data science and product teams to model data.
• Work with AWS cloud services to deliver scalable data solutions.
• Support CI/CD, testing, monitoring, and documentation across data environments.

Skills

Python

Data engineering

Spark

Airflow

CI/CD

Git

Education

Bachelor's degree in Computer Science/IT/Engineering

Tools

Docker

Kubernetes

Airflow

Kafka

Hive/Hadoop

Redshift

Athena

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.