HEAD OF DATA PRODUCT

I. JOB PURPOSE:
- The jobholder ensures that all systems meet the business/company requirements as well as industry practices.
- The jobholder integrate up-and-coming data management and software engineering technologies into existing data structures.
- The jobholder develop set processes for data mining, data modeling, and data production.
II. MAIN RESPONSIBILITY:    
1. Key accountabilities (1):
- Implement process improvements across requirement gathering, refinement and delivery of business requirements across the data analytics portfolio.
- Implement and grow data product management practices to support the development, enhancement, coordination and stakeholder communication of data analytics products and services.
- Mobilize a team of data product professionals to work across all business functions to collect, refine, prioritize and communicate effectively data analytics requirements, highlighting business value delivered from data capability.
- Collaborate with technology and people lead functions of Bank to ensure that capability is effectively aligned to broader roadmaps and can be delivered.
- Collaborate with technical leads to translate complex functional and technical requirements into detailed architecture, design and high performing capabilities with the Enterprise Data Lake.
- Identify, prioritize and deliver a backlog of Bank business wide products/solutions, which value will be delivered via the data lake and add ongoing commercial value to the business.
2. Key accountabilities (2):
- Analyze user requirements and manage demand and allocation for operational resources from DA.
- Ensure all delivery sign-off gates have been adhered to comply with data lake controls and data governance practices.
- Coordinate with HoD on regular bases to manage and prioritize product backlog.
- Perform budget estimation, plan, oversee and lead projects;
3. Key Accountabilities (3): 
Project Management
- Manage project conflicts, challenges and dynamic business requirements to keep operations running at high-performance.
- Work with team leads to resolve people problems and project roadblocks, conduct post mortem and root cause analyses to improve practices for maximum productivity.
Talent Development
- Mentor and coach junior members in team to enhance their data engineering capability.
- Identify and encourage areas for growth and improvement within the team and support with personal development plan.
III. SUCCESS PROFILE - QUALIFICATION AND EXPERIENCES:
1. Qualifications
- Bachelor's or Master’s degree in statistics, mathematics, quantitative analysis, computer science, software engineering or information technology.
2. Work Experience
- 15 years of relevant experience with modern data capability including scripting, developing, debugging and using big data technologies (e.g. Hadoop, Spark, Kafka or Tableau), database technologies (e.g. SQL, NoSQL, Graph databases), and programming frameworks (e.g. Python, R, Scala, Java) including 10+ years of equivalent managerial roles.
- Deep experience in designing and building dimensional ETL processes, data models, data warehouse concepts and methodologies, optimizing data pipelines and architecture
- Deep experience monitoring complex data issues, evaluating algorithmic approaches and examining data to resolve issues
- Deep understanding of Information Security principles to ensure compliant handling and management of data
- Advanced analytical and project management skills (DevOps, Extreme Programming, Agile, and Waterfall) fora variety of tasks or projects. Ability to deal with complex problems involving multiple facets, variables and situations where only limited standardization exists
- Extensive expertise in data technologies and the use of data to support software development, advanced analytics and reporting. Exposure to cloud technologies is a plus.
3. Other requirements
- Proven track-record in leading company-wide digital transformation initiatives and change management
- Mastery in Data & Analytics and is an industry expert on the latest data-related technology trends