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Head of Data Engineering Job Posting:

The Head of Enterprise Data Engineering is responsible for defining and executing the Bank's enterprise data engineering vision, strategy, and architecture. This executive leader oversees the end-to-end data ecosystem, ensuring scalable, secure, and regulatory-compliant data capabilities that power business growth, operational excellence, advanced analytics, and AI-driven innovation.

As a key technology influencer, this leader partners across business and technology functions to shape enterprise-wide data strategy, modernize the Bank's data platforms, and establish a future-state architecture that enables trusted, high-quality data from source systems through analytical and reporting environments. The role combines strategic leadership with operational execution, ensuring successful delivery of critical enterprise transformation initiatives while driving modernization across the data and analytics landscape.

The successful candidate will combine executive leadership, strategic vision, and deep technical expertise, with the ability to seamlessly transition between enterprise strategy and hands-on engagement in complex data architecture, engineering, AI, modernization, and platform-related challenges. This is not a pure oversight role; the leader must possess the technical credibility and practical experience to influence strategy, guide architectural decisions, and support resolution of critical technical issues when necessary.

Key Responsibilities

Enterprise Data Strategy & Architecture

• Define and advance the Bank's enterprise data strategy, architecture, and modernization roadmap aligned to business priorities and long-term technology objectives.
• Establish the architectural vision for enterprise data capabilities, ensuring scalability, resilience, security, and regulatory compliance.
• Lead the design and governance of end-to-end data architecture, including source systems, systems of record, data lineage frameworks, data integration platforms, data warehouses, and analytical environments.
• Influence enterprise-wide technology and business strategy through thought leadership, innovation, and strategic partnership with executive stakeholders.
• Serve as the senior technical authority for enterprise data engineering and architecture, providing guidance on complex architectural decisions, platform strategy, engineering standards, and modernization efforts.

Data Engineering & Transformation Leadership

• Lead large-scale data transformation initiatives currently in active delivery phases, ensuring successful execution of strategic modernization programs.
• Drive optimization of the enterprise data landscape by simplifying architectures, reducing technical debt, improving data accessibility, and enhancing platform performance.
• Oversee enterprise data engineering capabilities supporting mission-critical business operations and analytics.
• Ensure engineering excellence through the adoption of modern development practices, automation, data observability, and operational rigor.
• Provide hands-on leadership during critical delivery, architecture, and platform challenges, partnering directly with engineering teams to resolve complex technical issues and accelerate strategic outcomes.

Data & Analytics Platform Ownership

• Maintain executive accountability for the Bank's enterprise data and analytics technology portfolio, including platforms such as Databricks, Snowflake, Power BI, data management, and emerging AI-enabled capabilities.
• Develop and execute modernization strategies that advance cloud-based data platforms and next-generation analytical capabilities.
• Lead the evaluation and adoption of emerging technologies, ensuring the Bank's data ecosystem remains scalable, resilient, and positioned for future growth.
• Maintain deep knowledge of enterprise data platforms and architecture patterns to effectively guide platform evolution, technology investment decisions, and engineering execution.
  

AI, Data Innovation & Emerging Technologies

• Define how Artificial Intelligence and Generative AI capabilities are incorporated into the Bank's data engineering ecosystem.
• Partner with business and technology leaders to identify opportunities where AI can enhance data management, analytics delivery, decision-making, and operational performance.
• Establish foundational capabilities that enable responsible, scalable, and compliant AI adoption across the enterprise.

Regulatory & Risk Leadership

• Ensure all data engineering capabilities operate within a highly regulated financial services environment while meeting internal governance and external regulatory requirements.
• Serve as a senior leader during regulatory examinations, audits, and reviews involving enterprise data, data governance, controls, lineage, and reporting capabilities.
• Champion data quality, ownership, lineage, governance, and transparency across the organization.
• Implement controls and practices that support regulatory compliance, risk management, and trusted data usage throughout the enterprise.

Leadership & Organizational Development

• Lead a team of senior data engineering and technology leaders, including approximately five direct reports and an organization exceeding 200 professionals and contractors.
• Build high-performing teams that balance strategic vision with disciplined execution.
• Foster a culture of innovation, accountability, collaboration, and continuous improvement, working closely with our Chief Data Officer and our Enterprise Data and AI team.

Required Qualifications

• A combined minimum of 15 years' higher education and/or work experience, including a minimum of 4 years' engineering and/or architecture experience and 11 years' large technology management / program leadership experience including people management
• Demonstrated leadership experience overseeing large-scale data engineering organizations, preferably within complex, highly regulated industries.
• Proven experience leading enterprise data modernization and transformation initiatives from strategy through execution.
• Deep expertise with modern data platforms, including:
  • Databricks
  • Snowflake
  • Enterprise Data Warehousing
  • Data Management & Governance
  • Business Intelligence Platforms (Power BI or equivalent)
  • Cloud Data Architectures

• Strong understanding of data exchange, data lineage, systems of record, data governance, metadata management, and end-to-end data lifecycle management.
• Experience engaging directly with regulators, auditors, and risk management functions.
• Demonstrated success influencing executive stakeholders and enterprise-wide technology strategy.
• Strong blend of engineering leadership and strategic business partnership capabilities.
• Capable of working on multiple projects of a complex nature
• Experience on large system enhancements, conversions, and production problem resolution
• Complete understanding of the system development life cycle

Preferred Experience

• Financial services or other highly regulated industry experience.
• Experience developing enterprise AI or Generative AI strategies within a data and analytics environment.
• Experience serving as a senior technology thought leader responsible for enterprise architecture, innovation, and modernization.

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