Director, Software Engineering

Role Overview:

The Director of Finance Systems Engineering is a technology and engineering leader responsible for delivering and evolving systems that enable critical Finance capabilities. Reporting to a Senior Director in IT, this role will lead teams responsible for enterprise planning and forecasting platforms, custom-built Finance solutions, and SaaS applications that complement the core SAP ERP ecosystem.

The Director will lead a multidisciplinary team that includes planning model builders, systems analysts/product owners/TPMs, and software engineering professionals. This leader will partner closely with Finance to translate business priorities and transformation objectives into scalable technology solutions that simplify processes, improve decision making, and enable greater use of data, automation, AI, and machine learning.

A key responsibility of the role is strengthening the team’s ability to connect Finance domain expertise with specialized data and machine learning capabilities, enabling Finance to translate its AI and ML objectives into scalable solutions.

The successful candidate will combine strong engineering and people leadership with Finance domain knowledge and experience across enterprise planning platforms, custom software development, SaaS solutions, integration architectures, data, and AI/ML technologies.

What you'll be doing:

Finance Systems Leadership & Business Partnership

• Lead multidisciplinary teams responsible for planning and forecasting platforms, custom Finance solutions, and Finance-related SaaS applications.
• Partner with Finance leaders to understand business priorities and translate Finance transformation objectives into technology strategies, roadmaps, and solutions.
• Own the technology portfolio and multi-year roadmap balancing business priorities, technical debt, platform lifecycle, and operational sustainability.
• Establish engineering and product practices that balance speed, business value, user experience, scalability, reliability, security, and maintainability.
• Develop strong partnerships with Enterprise Architecture, Data Engineering, ML Engineering, Integration, Infrastructure, Cybersecurity, and other technology teams to deliver cohesive end-to-end solutions.
• Manage strategic technology vendors and implementation partners to ensure successful delivery, operational excellence, and continuous innovation.
• Build and develop a high performing organization across model building, systems analysis/product ownership, and software engineering disciplines while fostering a culture of accountability, collaboration, innovation, and continuous learning.

Planning, Finance Applications & Software Engineering

• Provide technology leadership for enterprise-scale financial planning, budgeting, forecasting, and scenario-modeling solutions used across Finance.
• Lead the engineering, maintenance, and support of custom applications and services that address Finance-specific business requirements.
• Provide leadership for Finance SaaS applications adjacent to the core SAP ERP ecosystem.
• Ensure Finance solutions integrate effectively with SAP and the broader enterprise application and data ecosystem while maintaining appropriate architectural standards and controls.

AI, ML and Data Enablement

• Partner with Finance leaders to identify opportunities where data, AI, and machine learning can improve planning, forecasting, financial analysis, automation, and decision making.
• Assess capability gaps and establish development plans, role expectations, and ways of working that prepare the Finance Systems Engineering organization to collaborate effectively with Data Engineering and ML Engineering teams.
• Enable teams to translate Finance business problems and domain knowledge into well-defined data, AI, and ML use cases.
• Partner with specialized technology teams to incorporate enterprise data, predictive models, and AI/ML services into Finance applications and business processes.
• Define how Finance Systems Engineering will evaluate, adopt, and govern AI and ML capabilities available through enterprise applications, internal data and ML platforms, and approved external services.
• Help drive adoption and operationalization of AI/ML capabilities within Finance while ensuring alignment with enterprise architecture, data governance, security, privacy, and technology standards

What we're looking for:

• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience.
• 10+ years of progressive experience leading enterprise application or software engineering organizations in a large enterprise environment, including accountability for multidisciplinary teams, technology delivery, and operational performance.
• 5+ years leading through managers, including responsibility for organizational design, talent development, performance management, and succession planning.
• Demonstrated experience building and leading multidisciplinary teams across software engineering, enterprise applications, planning applications, systems analysis, product ownership, and technical program management
• Experience leading enterprise scale financial planning, budgeting, forecasting, and scenario-modeling platforms, including responsibility for platform strategy, delivery, lifecycle management, and operational performance.
• Strong understanding of Finance processes, particularly financial planning, budgeting, forecasting, and related Finance operations.
• Demonstrated ability to partner with senior business leaders, translate business and transformation objectives into technology strategy and execution, and own multi-year portfolio roadmaps that balance business priorities, technical debt, platform lifecycle, and operational sustainability.
• Strong understanding of software engineering, enterprise architecture, integration, data, and cloud concepts.
• Demonstrated ability to develop technical talent and build new capabilities within an engineering organization, including preparing teams to partner effectively with Data Engineering and ML Engineering and to operationalize data, AI, and machine learning capabilities.
• Strong executive communication, stakeholder management, and cross functional leadership skills.

Preferred Qualifications

• Experience with one or more enterprise-scale planning and forecasting platforms, such as Anaplan, Workday Adaptive Planning, or SAP Analytics Cloud, including solution design, model governance, integration, or platform administration.
• Experience leading software engineering teams building custom enterprise solutions using Golang, Java or comparable programming languages.
• Experience with event-driven and streaming architectures and enterprise integration patterns.
• Experience leading a portfolio of Finance SaaS solutions, such as Coupa, Rightsline, or comparable platforms, including vendor management, integration, lifecycle planning, and operational governance.
• Experience with SAP S/4HANA and integration of Finance applications and services with the core ERP environment.
• Experience in jointly delivering production AI or machine learning capabilities with Data Engineering and ML Engineering teams, including integration into enterprise applications or business processes.
• Understanding of how AI and machine learning can be applied responsibly to Finance use cases, including forecasting, predictive insights, anomaly detection, decision support, and process automation, with attention to data governance, security, privacy, and enterprise technology standards.
• Experience supporting technology enabled Finance transformation within a large, global organization.