At a glanceSummarised by Seekless from the posting.
Must have18
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
Use Cloudera Machine Learning (CML) environments for development, testing, and execution of Spark workloads
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
Strong hands-on experience with Sparkola
Strong hands-on experience with PySpark
Strong hands-on experience with SQL (complex queries, joins, performance tuning)
Working knowledge of CML (Cloudera Machine Learning)
Working knowledge of Sparkola Job Server
Working knowledge of QlikSense and/or Superset
Strong proficiency in MS Excel for data validation, analysis, and reconciliation
Experience working in agile delivery models with strong exposure to JIRA boards
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
Nice to have2
Experience in banking or financial services, especially in regulated data environments
Exposure to data governance, audit, lineage, and controls
Eligibility1
Ensure solutions comply with DBS risk, security, and data governance standards, including internal data controls
Skills
Sparkola
PySpark
SQL
CML
Sparkola Job Server
QlikSense
Superset
MS Excel
JIRA
Business Function
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. In Group CBG, we manage the majority of the Bank’s operational processes and inspire to delight our business partners through our multiple banking delivery channels
Key Accountabilities
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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.
Business & Stakeholder Engagement
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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.
Delivery Governance & Controls
•
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.
Required Skills for this rile (JD):
Technical Competencies
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Strong hands‑on experience with:
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Sparkola
•
PySpark
•
SQL (complex queries, joins, performance tuning)
•
Working knowledge of:
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CML (Cloudera Machine Learning)
•
Sparkola Job Server
•
QlikSense and/or Superset
•
Strong proficiency in MS Excel for data validation, analysis, and reconciliation.
Functional & Behavioral Competencies
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Experience working in agile delivery models with strong exposure to JIRA boards.
•
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.
Preferred (Good to Have)
•
Experience in banking or financial services, especially in regulated data environments.
•
Exposure to data governance, audit, lineage, and controls.