Data Engineer

at  ELLIOTT MOSS CONSULTING PTE LTD

JOB DESCRIPTION

We are seeking a talented and experienced Data Management and Analytics Specialist to join our team. The ideal candidate will have a strong background in data management, analytics, and engineering, with a focus on the investment and banking industry.
This role involves working closely with business users, data engineers, and data scientists to implement and support data solutions, ensuring compliance with enterprise data governance standards.

Requirements

• A degree in Engineering, Computer Science/Information Technology, or a related field from a recognized tertiary institution.
• At least 7 years of relevant experience in data management, data analytics, and data engineering, preferably within the investment and banking industry.
• Strong understanding of the principles, key controls, and processes related to data management, data integration, and data distribution.
• Proficient in programming languages such as Python, Java, SQL, etc.
• Familiarity with data virtualization tools such as Denodo is advantageous.
• Detail-oriented and meticulous in operational tasks.
• Capable of designing and implementing solutions, as well as performing code reviews.
• Excellent written and verbal communication skills.
• Strong interpersonal skills with the ability to interact with diverse stakeholders.
• Agile, quick learner, and adaptable to changes.
• A team player with strong analytical skills and a passion for solving complex problems.
• Experience with the Systems Development Life Cycle (SDLC) and/or Agile methodologies like Scrum and Kanban.

Key Responsibilities:

• Support the Central Data Service Layer (CDSL) project.
• Collaborate with business users (research analysts, quantitative strategists, end-users, etc.), data engineers, and data scientists to implement and support data solutions that facilitate common functions in the data lifecycle, such as data onboarding and data distribution.
• Contribute to, 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, including collation of metadata and analysis of system operations data (e.g., data quality metrics, usage levels of data distribution services).
• Perform data access control operations to ensure compliance with enterprise data governance and data handling standards.
• Serve as the Centre of Excellence for common data lifecycle services, defining standards and best practices, and designing process workflows to streamline operations and ensure compliance.
• Monitor, analyse, investigate, and resolve day-to-day operational incidents and provide advisory support to users.
• Identify opportunities for continuous improvement in assigned areas of work.
• Manage and maintain strong stakeholder relationships to ensure continuous support and knowledge for existing and future data lifecycle needs.

• Support the Central Data Service Layer (CDSL) project.
• Collaborate with business users (research analysts, quantitative strategists, end-users, etc.), data engineers, and data scientists to implement and support data solutions that facilitate common functions in the data lifecycle, such as data onboarding and data distribution.
• Contribute to, 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, including collation of metadata and analysis of system operations data (e.g., data quality metrics, usage levels of data distribution services).
• Perform data access control operations to ensure compliance with enterprise data governance and data handling standards.
• Serve as the Centre of Excellence for common data lifecycle services, defining standards and best practices, and designing process workflows to streamline operations and ensure compliance.
• Monitor, analyse, investigate, and resolve day-to-day operational incidents and provide advisory support to users.
• Identify opportunities for continuous improvement in assigned areas of work.
• Manage and maintain strong stakeholder relationships to ensure continuous support and knowledge for existing and future data lifecycle needs