• You are curious and passionate to build advanced Data and AI Solutions
• We are ambitious in transforming lives of customers using Data and AI Strategy!
• Together we will deliver innovative solutions at scale to our customers!

TECHNICAL SKILLS AND TOOLS:

• People Management : Demonstrated experience in managing and leading large technical teams in Data Engineering, Advanced Analytics and Data Management.
• Technical Leadership: Deep technical expertise in data management, data engineering, stewardship and cloud migration with focus on AWS Cloud will be desirable.
• Tooling: A core background in data engineering along with decent exposure to managing hands-on tools such as Python, SQL, and key AWS integration packages.
• Cloud Architecture: Demonstrated experience in developing, deploying, and monitoring on AWS infrastructures.
• CI/CD: Experience with version control and CI/CD pipelines such as GitHub is desirable.

• Drive the creation and delivery of high-quality, reusable data products for a specific Retail Bank domain
• Lead in collaboration with multiple crews within a specific Retail Bank domain in delivering against data strategies, drive roadmaps and business priorities.
• Promote data skills development and foster strong collaboration across teams.
• Collaborate with Domain Data Delivery Leads to define vision and strategy of a specific Retail Bank domain’s Data Products
• Define and implement data needs and governance mechanisms aligned to your domain’s business goals.
• Ensuring all Data Products adhere to RBS Data Office guidelines on scoring thresholds, risk controls, and the Delivery Playbook, and meet CDAO standards around data management, design, and metadata
• Standardise and scale the production of efficient, re-usable data products. Providing critical business context for Data Products to ensure they meet the needs of stakeholders and users
• Strengthen producer-consumer data relationships across BUs/SUs and act as your Domains’ conduit for Data Product Management
• Driving improvement of new or existing Data Products where uplift is required e.g., if it is no longer fit-for-purpose or does not meet the scoring threshold
• Promote best practices, knowledge sharing, and continuous learning in data within your Domain
• Provide thought leadership across Data, AI, and Analytics, mentoring Data Product professionals in your Domain
• Work with Domain leads to implement and adhere to group’s Data Management Policy across your Domain