Data Operations Engineer

Description

Responsibilities

• Design and implement scalable data pipelines and integration frameworks that enable reliable data exchange across campus systems, cloud platforms, third-party applications, and APIs.
• Manage medium to large data initiatives, coordinating activities across teams and ensuring solutions support departmental objectives.
• Implement and enhance established standards for data integration, automated validation, and data quality.
• Maintain and improve monitoring practices that improve pipeline reliability and deliver dependable, scalable data solutions.
• Analyze complex data challenges, identify root causes, and implement solutions that improve overall data ecosystem performance.
• Improve enterprise data workflows through performance tuning and automation.
• Promote reliable operations through continuous improvement and operational best practices.
• Partner with business and technical stakeholders to align data solutions with strategic objectives and ensure data is accessible, trusted, and actionable.
• Support data governance by implementing standards and promoting consistent data management practices.
• Provide technical leadership for enterprise data engineering and operations initiatives.
• Guide and mentor team members by providing coaching, reviewing work, and supporting skill development across the function.
• Develop and maintain documentation for data architecture, integration workflows, metadata, and operational procedures.
• Evaluate and recommend tools, technologies, and architectural approaches to enhance data capabilities and operational effectiveness.
• Exercise independent judgment in selecting methods and approaches for new assignments, ensuring alignment with departmental priorities.
• Perform other duties as needed.

Required Skills, Knowledge and Abilities

• Deep understanding of data warehousing (Snowflake Platform) and large-scale data processing.
• Strong understanding of enterprise data architecture principles.
• Strong programming and scripting skills (e.g., Python, Shell).
• Ability to evaluate complex systems and recommend effective, scalable architectural solutions.
• Strong knowledge of enterprise data governance and data quality practices.
• Demonstrated ability to manage medium to large cross-functional projects and coordinate successful delivery across teams.
• Ability to translate strategic objectives into technical solutions and actionable plans.
• Excellent communication skills, with the ability to collaborate effectively with technical and non-technical stakeholders across the organization.
• Build collaborative relationships across functional teams to coordinate data operations efforts and support successful project delivery.
• Strong organizational and problem-solving skills, with the ability to manage competing priorities in a dynamic environment.

Required Education, Experience and Benefits Summary

• 3-5 years experience working with enterprise data integration, ETL/ELT development, data pipelines, and data platforms required.
• Bachelor's degree required. 
• Experience with Snowflake platform required.
• Advanced proficiency in SQL and strong experience with complex data structures, relational and dimensional modeling.
• Advanced experience designing and implementing scalable ETL/ELT pipelines and data integration frameworks.
• Experience with metadata management and data privacy principles.
• Demonstrated expertise with Salesforce CRM and Python preferred.
• Experience with Informatica or Skyvia preferred
• Experience working in academic, non-profit, or advancement operations environment is highly desirable.

• 10 paid holidays per year.
• Accrue up to 22 vacation days a year.
• Traditional pre-tax 403(b) and Roth retirement plans available.
• 10% employer contribution to your retirement plan and immediate vesting.
• Health Savings Account- earn up to $700 annually towards medical expenses.
• Employer funded Preventative Dental and Vision insurance. 
• Tuition discounts on eligible programs at Purdue University and Purdue Global for qualified employees, spouses, and dependents.