Overview

Consumer Banking Group enables and empowers the bank with an efficient, nimble and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation.

Responsibilities

• Develop, enhance, and support data extraction, transformation, and validation processes using Sparkola, PySpark, and SQL.
• Build and manage batch and ad‑hoc data pipelines through Sparkola Job Server, ensuring stability, performance, and timely delivery.
• Use Cloudera Machine Learning (CML) environments for development, testing, and execution of Spark workloads as per DBS standards.
• Ensure datasets are accurate, traceable, and fit for consumption by downstream analytics and reporting platforms such as QlikSense and Superset.
• Engage with business users and analysts to understand functional requirements and translate them into technical logic and data models.
• Support production issues and data clarifications as required.
• Manage deliverables using JIRA, adhering to timelines, priorities, and change control processes.
• Ensure solutions comply with DBS risk, security, and data governance standards, including internal data controls.

Qualifications

• Strong hands‑on experience with:
• Sparkola
• PySpark
• SQL (complex queries, joins, performance tuning)
• Working knowledge of:
• CML (Cloudera Machine Learning)
• Sparkola Job Server
• QlikSense and/or Superset
• Strong proficiency in MS Excel for data validation, analysis, and reconciliation.
• Excellent communication and collaboration skills, with the ability to bridge business and technology discussions.
• Strong analytical thinking, attention to detail, and problem‑solving capability.
• Proactive, dependable team player with a learning mindset and resilience in a fast‑paced environment.
• Exposure to data governance, audit, lineage, and controls.