Data Engineering Manager, Sr

Old National Bank•Evansville, IN

1d•$98,400 - $199,000

About The Position

Old National Bank has been serving clients and communities since 1834. With over $70 billion in total assets, we are a regional powerhouse deeply rooted in the communities we serve. As a trusted partner, we thrive on helping our clients achieve their goals and dreams, and we are committed to social responsibility and investing in our communities through volunteering and charitable giving. We continually seek highly motivated and talented individuals as our people are critical to our success. In return, we offer competitive compensation with our salary and incentive program, in addition to medical, dental, and vision insurance. 401K, continuing education opportunities and an employee assistance program are also included in our benefit suite. Old National also offers a variety of Impact Network Groups led by team members who are passionate about driving engagement, creating awareness of diverse backgrounds and experiences, and building inclusion across the organization. We offer a unique opportunity to join a growing, community and client-focused company that is firmly rooted in its core values.

Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent work experience.
8+ years data Engineering (ETL/ELT, data pipelines, data lakes, data warehouses, and data integration solutions)
3+ years managing and leading data engineering teams (financial services/banking preferred)
3+ years cloud data platforms (e.g., Azure Databricks, Data Factory, Data Lake Storage, Synapse Analytics, or equivalent)
3+ years technical product owner/product manager for data products, platforms, or solutions using Scrum or Kanban
Expertise in building scalable, reliable, and secure data solutions using modern data engineering approaches (metadata-driven, event-driven, and API-driven).
Experience working with stakeholders on gathering requirements, defining user stories, and translating business needs into data solutions, with a focus on developing reusable and modular components.
Experience in scripting tools such as Python, C#, or PowerShell.
Experience in orchestration tools or job schedulers, such as Azure Data Factory, Airflow, or equivalent.
Experience in data modeling, data quality, data governance, and data security standards and best practices.
Experience in code repositories and version control tools such as Azure DevOps, Git, etc.
Experience in analytical and data visualization tools such as Power BI, Tableau, or equivalent.
Strong T-SQL proficiency including complex stored procedures, user-defined functions, and query optimization.

Nice To Haves

Experience with financial services data domains (e.g., customer, transaction, risk, or wealth data).

Responsibilities

Serve as the technical leader for the team's domain, providing architectural direction and ensuring technical excellence.
Collaborate with product owners, managers, and stakeholders to define and deliver data solutions that drive customer value.
Oversee design, development, testing, deployment, and maintenance of data products, platforms, or services within the team's scope.
Ensure quality, reliability, scalability, and security of delivered solutions.
Establish and enforce data engineering standards, best practices, and guidelines.
Ensure compliance with enterprise data architecture and governance frameworks.
Monitor, troubleshoot, and resolve data and technical issues within the team's domain.
Provide technical guidance, mentorship, and coaching to data engineers.
Foster a culture of innovation and excellence.
Lead and manage the data engineering team including hiring, onboarding, performance management, career development, and retention.
Define and communicate the team's vision, roadmap, and backlog in alignment with the Data Technology organization's strategy.
Ensure alignment with the Data Office and other stakeholders across the bank.
Provide technical guidance, mentorship, and coaching to develop team capabilities.
Foster a culture of innovation, collaboration, and excellence.
Define and execute a data engineering strategy supporting the bank's data vision and goals.
Align with enterprise data architecture and governance frameworks.
Manage end-to-end delivery of data solutions, from ideation to deployment and ongoing support.
Apply agile and lean principles and practices (Scrum, Kanban).
Establish and enforce standards, best practices, and guidelines within the team's domain.
Ensure compliance with enterprise data architecture and governance frameworks.
Drive operational excellence through monitoring, issue resolution, and continuous improvement.
Ensure data quality and security across all team deliverables.
Stay abreast of latest trends and technologies in data engineering, cloud platforms, and the team's domain area.
Evaluate and recommend new solutions, tools, and approaches.
Demonstrate technical passion and curiosity to explore and adopt new technologies.
Prepare and present data engineering reports, dashboards, and metrics to senior leadership and business partners.