- Data Product roadmap:
- Along with Domain Lead to define, articulate the product vision, strategy, and roadmap for data platforms and data products in alignment with the bank's strategic objectives and data governance frameworks.
- Conduct in-depth business analysis to identify data-driven opportunities, define key data use cases, and inform the evolution of the data platform.
- Collaborate with data consumers (IT, EDA, Business Units,…) to understand their analytical needs and translate them into actionable data product requirements.
- Discover and develop data initiatives and its corresponding budget yearly.
- Data Product/Platform Delivery & Adoption:
- Manage and deliver Data Initiatives of DPIS Domain yearly (up to 4 initiatives)
- Inspect the data product increment at the end of each Sprint/Phase and determine acceptance against defined quality metrics and business value criteria.
- Facilitate user acceptance testing (UAT) for data products and platform features, gathering feedback for continuous improvement.
- Monitor the performance and adoption of data products post-launch, gathering data and insights to inform future iterations and imrovements
- Explore and evangelize the adoption of new capabilities, including Generative AI for data interaction, product (e.g., Text-to-SQL,), within relevant business units.
- Data Platform Backlog Management:
- Create, refine, and maintain a clear, concise, and prioritized Product Backlog for data platform features, data ingestion pipelines, data quality rules, and analytical product enhancements.
- Translate complex data and business requirements into detailed User Stories, Epics, and Acceptance Criteria, ensuring clarity and readiness for the data engineering teams
- Continuously prioritize backlog items based on business value, regulatory compliance, data quality impact, technical feasibility, and strategic alignment.
- Stakeholder Collaboration & Data Management:
- Act as the primary liaison between business stakeholders (e.g., Fin, Risk, Retail, SME), IT divisions (e.g., ITCORP, Core Banking, DF), and the data development teams (SA, Dev, QA, Ops)
- Gather, analyze, and synthesize data requirements from various departments, resolving conflicts and making informed decisions that balance business needs with data platform scalability and governance.
- Champion data quality, data lineage, and data security principles, ensuring adherence to the bank's data governance policies across all data products and platforms (DIH, Datalake, ODS).
- Data Development Team Enablement:
- Actively participate in Agile stage (Sprint Planning, Daily Scrum, Sprint Review, Retrospective) for data engineering and data consumer teams to guide and support development efforts.
- Provide timely clarifications and answer questions from the data teams regarding data models, business rules, and integration logic (e.g., for T24 Parsing, Movement Reports, complex CRs).
- Ensure the team has a clear understanding of "What" data products/platform features need to be built and "Why" they are important for business value.
Other tasks assigned by DPIS Manager
Trình độ Học vấn
Educational Qualifications
- A Bachelor's degree is required. Preferred fields include Computer Science, Information Technology, Data Science, Business Administration, Finance, Economics, or a related quantitative field
- Certified Scrum Product Owner (CSPO) or Professional Scrum Product Owner (PSPO), PMP are highly desirable
Các Kinh nghiệm liên quan/ Relevant Experience
- Minimum of 5 years of experience working in a Product Owner, Product/Project Manager, or Senior SA/BA role within an Agile/Scrum environment.
- Experience managing the entire product lifecycle from ideation, development, deployment, to post-launch optimization
- Proficiency with backlog management tools (e.g., Jira, AWS DevOps) and prioritization techniques
- Experience working with Big Data platforms such as Data Lakes (e.g., on AWS S3), Data Warehouses (e.g., Amazon Redshift, Snowflake), and Operational Data Stores (ODS).
- 2+ year experience in understanding of data architecture, data modeling, ETL/ELT processes, and both batch and streaming data processing technologies (e.g., Kafka, Flink, Spark).
- Experience working with data governance tools and processes, data quality management, and data security principles.
- Experience working within the banking or financial services industry is a significant advantage, especially with products and processes related to data platforms
Kiến thức/ Chuyên môn có liên Quan
Relevant Knowledge/ Expertise
- In-depth knowledge of identifying, analyzing, and effectively engaging diverse stakeholders, including senior leadership, business units, and technical teams
- Expertise in negotiation tactics and conflict resolution strategies to facilitate consensus, resolve disagreements
- Understanding of methodologies and practices that foster effective teamwork
- Careful, attention to detail, logical thinking
