Data Engineer

Roles & Responsibilities

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, analyse, investigate, and resolve day-to-day operational incidents and provide advisory to users.
• Identify opportunities for continuous improvement in the assigned area of work.
• Manage and maintain strong stakeholder relationship to ensure continuous support and knowledge for existing and future data lifecycle needs.

Requirement:

• Possess a degree in Accounting, Finance, Engineering, Computer Science/Information Technology or related fields from recognized tertiary institution.
• At least 5 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.
• Familiar with data visualization tool (e.g. Tableau, PowerBI) and data virtualization technology 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 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 in the Systems Development Life Cycle implementation methodology (SDLC) and/or Agile methodologies like Scrum and Kanban.

Roles & Responsibilities

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, analyse, investigate, and resolve day-to-day operational incidents and provide advisory to users.
• Identify opportunities for continuous improvement in the assigned area of work.
• Manage and maintain strong stakeholder relationship to ensure continuous support and knowledge for existing and future data lifecycle needs.

Requirement:

• Possess a degree in Accounting, Finance, Engineering, Computer Science/Information Technology or related fields from recognized tertiary institution.
• At least 5 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.
• Familiar with data visualization tool (e.g. Tableau, PowerBI) and data virtualization technology 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 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 in the Systems Development Life Cycle implementation methodology (SDLC) and/or Agile methodologies like Scrum and Kanban.