Manager, Data Platform Engineernew

We are seeking an experienced Manager, Data Platform Engineer and AI Tools within Technology, with 8+ years of experience to lead high-end software development and testing capability, to support the business. The candidate should be a seasoned and hands-on technical manager with expertise in system architecture, development, release management, support and agile/scrum delivery. The candidate should be an experienced and dynamic individual overseeing end-to-end project deliveries and ensure exceptional client satisfaction. The ideal candidate will possess a strategic mindset, strong leadership abilities, and a proactive approach to delivery excellence.

Key Accountabilities and main responsibilities

Strategic Focus 

• Drive the evolution of the Enterprise Data Platform to support scalable, secure, and high value data products that enable business growth across Investor Services and Capital Analytics.
• Accelerate delivery of new analytics and AI-driven capabilities through rapid prototyping, modern engineering practices, and seamless integration of emerging technologies.
• Establish enterprise grade data governance, stewardship, and semantic frameworks to democratize data access while maintaining compliance, quality, and control.

Operational Management 

• Oversee end-to-end data platform operations, ensuring high availability, performance, and reliability across development, staging, and production environments.
• Implement and enforce operational controls including monitoring, alerting, logging, incident management, and adherence to SDLC and Change Management processes.
• Optimize platform efficiency and cost management by continuously reviewing compute usage, storage patterns, and pipeline performance to drive operational excellence.
• Ensure robust data quality and governance operations, including validation checks, lineage maintenance, access management, and compliance with internal security standards.
• Review requirements and prototypes from the company’s Data and Analytics team.
• Work as part of an agile team to design, plan and rapidly build new solutions to increase the business value of the enterprise data platform.
• Democratize ownership of data by integrating user-facing data stewardship and semantic model tools.  
• Coordinate delivery of client requests and production fixes (also strategic).
• Continually evolve our data platform to provide data integration, transformation, presentation and analysis capabilities to enable the creation of new data products and services.

People Leadership 

• Collaborate and work closely with business partners, Business Analysts, Project Managers, and other stakeholders.
• Coordinate delivery of client requests and production fixes (also strategic).

Governance & Risk 

• Familiarity with secure coding practices and encryption techniques for sensitive financial data.
• Ensure adherence to enterprise data governance, security, and regulatory requirements, implementing proper access controls, encryption, data masking, lineage tracking, and compliance with SDLC and Change Management policies.
• Identify, assess, and mitigate operational and technology risks across data pipelines, cloud services, and platform components by establishing proactive monitoring, incident response protocols, and regular risk reviews.
• Strengthen governance frameworks by embedding data quality standards, audit readiness, policy enforcement, and documentation practices to reduce operational vulnerabilities and ensure consistent, compliant data operations.

The above list of key accountabilities is not an exhaustive list and may change from time-to-time based on business needs.

Experience & Personal Attributes

Experience 

• Candidate should possess at least 8+ years of relevant experience and an Engineering degree / BS degree.
• Strong understanding of data modelling, data transformation techniques and data presentation.
• Experience automating tasks with scripting technologies
• Strong SQL and Python scripting skills
• Snowflake Openflow
• Cloud platform exposure preferred (AWS, Azure, Snowflake).
• Application of artificial intelligence and machine learning to Business Intelligence or Analytics use cases 
• Experience with BI, Analytics and data presentation tools (Power BI, Tableau, Sigma, Omni or similar technologies).
• Application of artificial intelligence and machine learning to Business Intelligence or Analytics use cases 
• Experience preparing data for use by AI and build-out of Semantic layers.
• Experience providing context to Large Language models through RAG or MCP
• Fundamental understanding of accounting principles. 
• Financial Domain Knowledge: Understanding of accounting principles, risk management, and stock market operations.
• Identifying and resolving software defects or performance issues in Data Platform.
• Experience working with financial data, including secure data exchange and performance optimization.
• Experience with CI/CD pipelines (also strategic, but relevant for governance in regulated environments).
• Experience with cloud services like Azure (security and compliance considerations).
• Personal Attributes
• Ability to work independently or as part of a team
• Strong analytical and problem-solving skills required, and the ability to complete projects with little or no supervision.
• Strong oral and written communication skills 
• Ability to guide and mentor junior team members on solution architecture and other technical topics.
• Ability to work as part of a cross-cultural team
• Must be able to operate in a stressful, quality and deadline driven environment while maintaining strict attention to detail and the ability to prioritize issues appropriately while managing multiple assignments. 
• Ability to take initiative and critically analyse processes and procedures. 
• Continuous improvement focus, with the ability to identify risks, cost efficiencies, and operational improvements
• Strong presentation and communication skills with ability to communicate clearly and effectively at all levels
• Ability to effectively liaise with senior-level stakeholders to communicate issues, risks, and solutions
• Self-driven and motivated with a focus on operational efficiency and continuous improvement