Data Engineer III

Old National Bank•Lake Elmo, MN

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. We are seeking a Data Engineer with expertise in Azure, AWS, Databricks, and Python to design, build, and optimize scalable data pipelines and products. This role will focus on developing modern cloud-based data solutions that support analytics, reporting, system integrations, and AI/ML. The ideal candidate will leverage Python and SQL for automation and data processing while ensuring reliability, security, and performance across platforms. Working closely with analysts, data scientists, and business stakeholders, this position plays a key role in delivering high-quality and efficient data solutions. Salary Range The salary range for this position is $77,900 - $153,000 per year plus bonus. The base salary indicated for this position 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 a number of factors, including the specific responsibilities of the position, the candidate’s relevant skills and professional experience, educational qualifications, and geographic location. Key Competencies for Position Ability to work independently and be able to collaborate and guide other team members. Critical thinking and problem-solving skills to ensure the right-sized solution is developed for the task at hand. Technical passion to move the bank towards modern data platform principles.

Requirements

Bachelor’s degree required.
Over 5 years of experience in data engineering, including developing ETL/ELT, data pipelines, data lakes, data warehouses, and data integration solutions.
Over 3 years of experience on data engineering teams, preferably in a financial services or banking domain.
3-5 years' experience Cloud platforms (AWS, Azure, GCP, Databricks,Snowflake) Databricks preferred and Python programming or advanced SQL coding and performance tuning.
Experience in a product mindset, using agile frameworks such as Scrum or Kanban.
Expertise in building scalable, reliable, and secure data products and platforms, using metadata driven, event driven, and API driven approaches.
Experience in scripting tools such as Python.
Experience in orchestration tools or job schedulers, such as Azure Data Factory, Airflow, or Luigi.
Experience in data modeling/mastering, 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.
Very good working experience of T-SQL.
Proficiency in complex stored procedures, user defined functions, and query optimization.

Nice To Haves

Experience in working with Salesforce data and digital banking data is a plus.
Experience in analytical and data visualization tools such as Power BI, Tableau, or Qlik.

Responsibilities

Design, development, and maintenance (enhancements and maintenance) of enterprise data products and pipelines.
Design and development of repeatable frameworks and functions to be leveraged by other data engineers within the bank.
Focus on Operational Excellence- ensuring we are monitoring, validating, and communicating the health and status of our data products.
Collaborate with Enterprise Architecture, Info Security and Data Governance organizations.
Confer with relevant team members where necessary.
Study systems flow, data usage, and work processes.
Deliver functional data products that have been thoroughly tested.
Follow the development team’s SDLC process.
Accurately estimate time required to complete projects and tasks.
Meet mutually agreed upon deadlines for completion of modules throughout the program development.
Work closely with the existing platform owners to design, model, develop, and maintain existing and new objects/products required for all business solutions.