Senior Data Engineer - OCBC

As Singapore's longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires.

Today, we're on a journey of transformation. Leveraging technology and creativity to become a future-ready learning organisation. But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia's leading financial services partner for a sustainable future.

We invite you to build the bank of the future. Innovate the way we deliver financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can. Or simply enjoy a vibrant, future-ready career.

Your Opportunity Starts Here.

Why Join

You'll be part of a collaborative team that values creativity, innovation, and continuous learning.

How you succeed

We are seeking a highly skilled and motivated Senior Data Engineer with expertise in cloud-native data engineering on any major cloud platform. The ideal candidate will have hands-on experience with Spark, PySpark, Iceberg, streaming systems, and open data catalogue/governance frameworks.

This role is suitable for individuals with minimum 3 years of relevant industry experience and have strong fundamentals, high learning agility, and a passion for building modern data systems.

What you do

• Design and build scalable, reliable data pipelines using native services provided by the chosen cloud platform.
• Implement data lakehouse solutions using Apache Iceberg and open, interoperable metadata/catalogue frameworks.
• Modernize existing data processing pipelines with cloud-first architectural principles.

• Develop and maintain real-time streaming pipelines using the platform's native streaming, messaging, and event ingestion services.
• Build structured streaming logic using Spark Structured Streaming or equivalent cloud-native stream processing tools.

• Participate in the migration of complex SQL workloads and legacy processing systems into a cloud-native architecture.
• Optimize SQL and transformation logic to leverage cloud-scalable compute and storage.

• Build end-to-end ETL/ELT workflows using Python and Unix/Linux shell scripting.
• Write efficient SQL for complex data transformations and analytics.
• Develop automated data quality checks, validation processes, and operational monitoring.

• Leverage open-source catalogue/governance solutions (e.g., Open Data Catalogue, OpenMetadata, DataHub) to ensure lineage, metadata capture, and data accessibility.
• Support data governance practices across domains and teams.

• Work closely with analysts, data scientists, and stakeholders to deliver robust, scalable data solutions.
• Troubleshoot pipeline issues, ensure data reliability, and optimize processing performance.
• Continuously explore new technologies and best practices within the data engineering ecosystem.

• Strong hands-on experience with Apache Spark and PySpark.
• Practical experience with Apache Iceberg table format for data lakehouse architectures.
• Experience with open-source data catalogue/governance frameworks.
• Proficiency in SQL, including handling complex transformation logic.
• Strong skills in Python for data engineering, orchestration, and automation.
• Solid understanding of Unix/Linux shell scripting.
• Experience with one major cloud platform and its native services for:
• Storage
• Compute
• Data processing
• Streaming/event ingestion
• Workflow/orchestration
• Familiarity with relational databases, data lakes, and data warehouse concepts.
• Good understanding of cloud-native open technology stacks and distributed data systems.

• Highly collaborative, with strong teamwork abilities.
• Excellent analytical and problem-solving skills.
• Clear communication skills for both technical and non-technical audiences.
• Adaptable, curious, and eager to learn new tools and technologies.
• Detail-oriented with strong documentation habits.
• Good prioritization and time management skills.
• Self-driven and accountable for high-quality delivery.

• Bachelor's degree or Diploma in Computer Science, Engineering, IT, or related field.
• Relevant cloud data engineering certification, such as:
• Professional Data Engineer
• Certified Data Engineer Associate
• Other platform-specific Data Engineering certifications
• Familiarity with Docker, Kubernetes, and containerized data workflows.
• Experience with CI/CD pipelines, DevOps workflows, and version control systems such as Git.
• Knowledge of lakehouse architectures, distributed systems, or data mesh principles.

Who we are

As Singapore's longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires.

But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia's leading financial services partner for a sustainable future.

Your Opportunity Starts Here.

Competitive base salary. A suite of holistic, flexible benefits to suit every lifestyle. Community initiatives. Industry-leading learning and professional development opportunities. Your wellbeing, growth and aspirations are every bit as cared for as the needs of our customers.