Associate Director, Data Engineering

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GENERAL FUNCTION:
The Associate Director, Data Engineering will have the responsibility of people leadership for a minimum of five to a maximum of ten FTE (full-time Fifth Third employees), with all the responsibilities that people management and leadership entail and will interact and influence leaders across the organization drawing connections to all strategic priorities. The main responsibilities will include developing and coaching employees, removing impediments to performance, developing ways to enable collaboration, being a leader of the data engineering craft, sharing best practices, guiding teams in the design and implementation of optimal data solutions aligned with enterprise architecture principles, and executing insourcing strategies. The Associate Director will handle performance review, compensation and other core human resources processes for their team and will need to work collaboratively across the Technology team and other internal groups.

Responsible and accountable for the identification of risk by openly exchanging ideas and opinions, elevating concerns. They personally follow policies and procedures as defined and are accountable for always doing the right thing for customers and colleagues. The incumbent ensures that their actions and behaviors drive a positive customer experience. While operating within the Bank's risk appetite, the role achieves results by consistently identifying, assessing, managing, monitoring, and reporting risks of all types.

ESSENTIAL DUTIES & RESPONSIBILITIES:

• Develop and coach employees to meet the needs of the organization while balancing personal development of the employees.
• Actively participate in the hiring of experienced and college graduate level employees.
• Solicit feedback from key team members to understand the performance of team members and provide that feedback to the employee in a timely manner.
• Work with other leaders within the organization to identify and problem solve issues that are preventing employees from performing effectively.
• Identify organizational needs/gaps and propose solutions to resolve.
• Be a leader of their particular craft to provide insight on best practices and provide insight on future direction of the craft for the organization.
• Apply and deploy multiple approaches to remove organizational impediments (e.g. cultural barriers, logistic challenges, mindset shifts, etc.).
• Facilitate communication, cooperation, and collaboration across the organization, including continuous feedback loops.
• Work to improve the effectiveness of all roles of the organization, fostering self-organization, learning and growth.
• Challenge current processes, identifying opportunities for increased efficiency, effectiveness, and consistency to drive continuous improvement in results.
• Build a trusting and positive culture where issues are resolved in a safe environment.
• Partner with cross-functional stakeholders (e.g., Product, Risk, Compliance, Analytics) to translate needs into scalable data solutions that support strategic priorities.
• Drive adoption of the bank’s modern data strategy by fostering innovation, ownership, and continuous learning within the team.

SUPERVISORY RESPONSIBILITIES:

Duties include, but are not limited to performance management, focused investment in people growth and direction, feedback coaching and disciplinary activities (if needed), succession planning, recognition of employees, etc.

MINIMUM KNOWLEDGE, SKILLS & ABILITIES REQUIRED:

• Proven track record of leading/mentoring scaled data engineering teams through modernization and conversion initiatives, including migration from legacy systems to modern cloud-based architectures and tooling.
• Experience designing and implementing scalable data pipelines and architectures using modern tools such as Snowflake, dbt, DataStage, and cloud-native services (e.g., AWS, Azure, GCP).
• Familiarity with data domains such as commercial lending, underwriting, and risk/regulatory reporting is highly desirable.
• Experience in enterprise data architecture and designing scalable data solutions across complex ecosystems is required
• Deep understanding of all software lifecycle development disciplines - Project Management, Requirements Management, Analysis & Design, Quality Assurance & Testing, Implementation, Deployment, Configuration & Change Management.
• Typically, will have at least eight years of hands-on experience in Data Engineering.
• Bachelor’s or advanced degree in Computer Science/In