Enterprise Data Strategist

Key Focus Areas

• Strategy Over Architecture: The team is seeking a candidate with a demonstrated Data Strategy background who can look horizontally across the enterprise to map out a future path forward. A pure data architect will not be successful here; however, foundational data architecture experience is highly valuable for context and alignment.

Main Areas of Responsibility

• Define and help execute the enterprise data strategy in alignment with business priorities, regulatory expectations, and long-term technology goals.
• Guide modernization efforts for enterprise data platforms, including cloud-aligned architectures, scalable integration approaches, and reusable data services.
• Evaluate current-state data ecosystems and recommend improvements to architecture, tooling, operating models, and governance processes.
• Support the translation of business requirements into enterprise data designs, roadmaps, and implementation guidance for delivery teams.
• Develop and maintain enterprise data architecture standards, principles, and target-state blueprints across domains, platforms, and integration patterns.
• Partner with business stakeholders, data owners, application teams, and technology leaders to identify data capabilities, gaps, and opportunities for improvement.
• Lead data architecture activities including conceptual, logical, and physical data modeling, data flow design, lineage considerations, and information lifecycle planning.
• Establish and promote best practices for data governance, metadata management, master/reference data, data quality, and data security in collaboration with control and compliance partners.

Requirements & Qualifications

• Education: BSc or MSc degree in Computer Science, Information Systems, Data Management, or a related discipline.
• Data Strategy & Architecture: Strong experience in enterprise data strategy, data architecture, and information management within complex enterprise organizational environments.
• Technical Deep Dive: Robust understanding of data architecture disciplines including enterprise data modeling, canonical models, data integration, metadata management, and data lifecycle design.
• Governance & Platforms: Experience defining and implementing data governance frameworks, data quality controls, and stewardship models. Strong knowledge of relational/non-relational data platforms and data warehousing concepts.
• Integration: Experience with data integration approaches, APIs, event-driven patterns, ETL/ELT processes, and distributed data architectures.
• Soft Skills: Positive, collaborative attitude with excellent written and verbal communication skills; ability to influence stakeholders across business and technology functions.

Nice to Have Attributes

• Experience within financial services or other highly regulated industries.
• Familiarity with enterprise architecture frameworks and data governance tools.
• Experience supporting cloud data modernization, data platforms, or enterprise analytics transformation initiatives.