Mandatory Skills
- Possess a degree in Engineering, Computer Science/Information Technology or related fields from recognized tertiary institution.
- At least 3 years of relevant experience in data management, data analytics, data engineering user. Preferably within investment and banking industry.
- Good understanding of the principles, key controls and processes relating to data management as well as data integration and data distribution.
- Good knowledge and experience in programming languages such as Python, Java, SQL etc.
- Familiarity with data virtualization tool such as Denodo is advantageous.
- Good at working with details and is meticulous for operations.
- Able to design and implement solution, and perform code review.
- Excellent written and verbal communication skills.
- Strong interpersonal skill and able to interact with diverse stakeholders.
- Agile, fast learner and able to adapt to changes.
- Good team player, with strong analytical skill and enjoy complex problem solving.
- Experience with the Systems Development Life Cycle (SDLC) implementation methodology and/or Agile methodologies like Scrum and Kanban.
Skillsets (Good to have)
Brief Job Description
- Support Central Data Service Layer (CDSL) project
Responsibilities:
- Work closely with business (research analysts, quantitative strategist, end-users, etc.), data engineers, data scientists to implement and support data solutions that support common functions in the data lifecycle e.g. data onboarding, data distribution.
- Contribute, influence, and validate the design of lifecycle data solutions to ensure they meet both business and operational needs.
- Manage day-to-day operations for lifecycle data solutions such as collation of metadata, analysis of system operations data (e.g. data quality metrics, usage level of data distribution services).
- Perform data access control operations to ensure data ingested and distributed comply with enterprise data governance and data handling standards.
- Function as the Center of Excellence for the common data lifecycle services offered, defining standards and best practices, and designing process workflows to smoothen operationalization and to ensure compliance.
- Monitor, analyze, investigate, and resolve day-to-day operational incidents and provide advisory to users.
- Identify opportunities for continuous improvement in assigned area of work.
- Manage and maintain strong stakeholder relationship to ensure continuous support and knowledge for existing and future data lifecycle needs.
