Data Engineering Manager, Sr

About the role

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.

Responsibilities

• Lead a data engineering team within the Data Technology organization, overseeing the development and delivery of technical solutions that support the bank's data strategy.
• Set vision and direction for the team's domain, ensuring alignment with the Data Office and stakeholders across the bank and IT.
• Collaborate with other product owners and managers to deliver customer value.
• Guide and mentor data engineers, fostering a culture of innovation and excellence, and promote best practices in data engineering and agile methodologies.
• 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.
• 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.
• Define and execute a data engineering strategy supporting the bank's data vision and goals.
• Manage end-to-end delivery of data solutions, from ideation to deployment and ongoing support.
• Apply agile and lean principles and practices (Scrum, Kanban).
• 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.
• Prepare and present data engineering reports, dashboards, and metrics to senior leadership and business partners.
• May require travel to other branch or meeting locations.

Key Competencies

• Develops Talent: Advocates for talent development as an organizational imperative, cultivates a diverse succession pipeline, and leverages talent as a corporate resource.
• Promotes Change: Explains the business need and benefits of change, engages stakeholders, and manages risk associated with change.
• Strategy in Action: Develops and communicates a clear vision and strategy, challenges the status quo, and aligns efforts with strategic goals.
• Compelling Communication: Conveys messages logically and succinctly, tailors communication to the audience, and encourages open exchange of ideas.
• Makes Decisions & Solves Problems: Analyzes data to define problems, collaborates to create strategies, and aligns resources for maximum impact.
• Delights Clients: Cultivates a client-focused culture, empowers accountability, and nurtures client relationships to meet needs and add value.
• Leads Inclusively: Champions diversity and inclusion, challenges bias, and promotes an environment of trust and self-awareness.
• Personifies ONB Culture: Instills confidence in actions aligned with Old National’s culture, vision, and values, inspiring others to contribute to long-term success.

Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent work experience.
• 8+ years in 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 with cloud data platforms (e.g., Azure Databricks, Data Factory, Data Lake Storage, Synapse Analytics, or equivalent).
• 3+ years as a technical product owner/product manager for data products, platforms, or solutions using Scrum or Kanban.

Skills

• 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 to gather requirements, define user stories, and translate business needs into data solutions.
• Experience with scripting tools such as Python, C#, or PowerShell.
• Experience with 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 with code repositories and version control tools such as Azure DevOps, Git, etc.
• Experience with 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.
• Experience with financial services is a plus.

Benefits

• Competitive compensation with salary and incentive program.
• Medical, dental, and vision insurance.
• 401K retirement plan.
• Continuing education opportunities.
• Employee assistance program.
• Impact Network Groups led by team members to drive engagement, awareness of diverse backgrounds, and inclusion.

Pay

The salary range for this position is $98,400/yr - $199,000/yr plus bonus. The base salary reflects the compensation range applicable to all levels of the role across the United States. Actual salary offers within this range may vary based on factors such as specific responsibilities, candidate’s skills and experience, educational qualifications, and geographic location.