Data Engineer – Banking Data Infrastructure

About the role

The Data Engineer will be a key contributor to the bank’s data strategy, designing, building, and maintaining a robust, scalable, and secure data infrastructure. This role supports business intelligence, regulatory reporting, advanced analytics, and machine‑learning initiatives across the institution.

Key responsibilities

• Design and construct data pipelines that move high‑quality data from source systems to consumption layers.
• Maintain and optimise large‑scale relational databases and data‑warehousing solutions.
• Implement and manage Big Data technologies such as Apache Spark and Apache Kafka.
• Develop cloud‑based data solutions on AWS, Azure, or GCP.
• Orchestrate ETL workflows using tools like Airflow and ensure version control with Git.
• Collaborate with business analysts to deliver data models and visualisations in Power BI.
• Ensure compliance with financial regulations and internal data‑governance standards.

Required profile

• First‑degree in Computer Science, Engineering, Information Systems or a related quantitative field.
• 5‑7 years of professional experience in data engineering.
• Expert proficiency in SQL and strong programming skills in Python or Scala.
• Hands‑on experience with Big Data frameworks (Spark, Kafka) and at least one major cloud platform.
• Familiarity with data‑warehousing concepts, ETL scheduling, and orchestration tools.
• Solid understanding of version control (Git) and data visualisation with Power BI.

Required skills

• SQL
• Python
• Scala
• Apache Spark
• Apache Kafka
• AWS / Azure / GCP
• Data Warehousing
• ETL orchestration (Airflow)
• Git
• Power BI