Data Engineering Sr Manager

Unclassified - Columbus, OH

Full-time - Senior

Columbus, OH

About the position

The Data Engineer Senior Manager will lead the design, development, and deployment of data engineering solutions to support enterprise goals and drive innovation. This role involves managing a team of data engineers, ensuring data quality, and collaborating with various stakeholders to refine data requirements for analytics initiatives. The position is crucial for operationalizing data necessary for the company's data and analytics strategies, aiming to position Huntington as the best-performing regional bank in America.

Responsibilities

• Lead and develop a team of Data Engineers.
• Set the strategy and vision for data engineering.
• Architect, create, and maintain data pipelines.
• Collaborate with data science teams and business analysts to refine data requirements.
• Work with data governance teams to promote content for governed reuse.
• Provide leadership, coaching, and mentoring to team members.
• Identify required roles, skills, and knowledge to achieve organizational goals.
• Evaluate tools with stakeholders to prioritize analytics use cases.
• Plan and ensure execution of work and achievement of team goals.
• Anticipate and analyze technology trends and their impacts.
• Coach individuals through change and serve as a role model.

Requirements

• Bachelor's Degree in computer science, statistics, or a related field.
• 10+ years of experience in data management disciplines including data integration, modeling, optimization, and data quality.
• 10+ years of technical leadership and management experience on data-centric products.
• Experience with database programming languages and advanced analytics tools.

Nice-to-haves

• Expert experience with data engineering tooling (e.g., Glue, Lambda, Athena, AWS).
• Expert knowledge of BI software tools.
• Expert experience with open-source and commercial data science platforms.
• Experience with Agile methodology.
• Demonstrated ability to influence both technical and non-technical audiences.
• Strong experience with various Data Management architectures and processes.
• Experience in working with large, heterogeneous datasets.

Benefits

• Equal employment opportunities for all individuals.
• Commitment to diversity and inclusion in the workplace.