Position Overview
Analytics, Institutional Research, & Effectiveness (AIRE) at the University of Kansas brings together analytical and technical staff to support KU's data strategy and data-informed decision making. The Senior Data Engineer plays a critical role in designing, building, and maintaining complex data systems, including data pipelines, data warehouses, and data lakes. This role is integral to enabling advanced analytics, business intelligence, and AI/ML-powered insights across the institution.
The Senior Data Engineer will work closely with cross-functional teams to ensure scalable, secure, and reliable data infrastructure and contribute to KU's mission of fostering self-service analytics and data governance.
Job Description
Development (50%)
- Design, develop, and maintain scalable ETL/ELT pipelines integrating data from diverse internal and external sources.
- Develop and optimize SQL-based processes to support data loading, transformation, and validation tasks.
- Architect and implement cloud-based data solutions using platforms such as AWS or Azure.
- Maintain and enhance KU's Data Warehouse and Data Lake environments to support analytics, dashboards, and operational reports.
- Support AI/ML model integration pipelines and prepare data for model training, scoring, and inferencing.
- Collaborate with BI Analysts, Data Scientists, and business stakeholders to translate requirements into performant data engineering solutions.
- Build and maintain APIs and web services for data access, exchange, and automation.
- Maintain and document data workflows, source-to-target mappings, and architecture diagrams in accordance with data governance policies.
- Ensure metadata capture and compliance with KU's data catalog and dictionary.
Application/Integration Support (20%)
- Provide production support for ETL/ELT jobs, data pipelines, and cloud-based infrastructure.
- Troubleshoot issues related to data ingestion, transformation, and availability.
- Monitor job performance and system health, coordinating with IT operations as needed.
- Participate in upgrade cycles for ETL tools, cloud platforms, and database systems.
- Support version control, code deployment, and CI/CD practices for data applications.
Leadership (15%)
- Mentor junior data engineers and guide technical implementation best practices.
- Lead code reviews and drive architectural decisions for data projects.
- Communicate project progress, risks, and technical challenges to stakeholders.
- Participate in sprint planning, retrospectives, and Agile ceremonies.
Testing and Validation (10%)
- Define and execute data validation strategies for all data pipelines and models.
- Implement audit controls, data quality checks, and reconciliation procedures.
- Collaborate with QA teams and business users for UAT and production validation.
Other Projects (5%)
- Participate in campus-wide data initiatives, pilot projects, and tool evaluations.
- Contribute to continuous improvement and innovation in KU's data engineering practices.
Required Qualifications
- Bachelor's degree in computer science, Information Technology, Engineering, Mathematics, Statistics or a related field and ten (10) years of relevant professional experience OR Master's degree with eight (8) years of experience.
- Over ten (10) years of hands-on experience with SQL and database systems (e.g., Oracle, PostgreSQL, SQL Server, MySQL).
- Experience in data warehousing and data lake architectures.
- Over eight (8) years of experience using Python for scripting, automation, and data manipulation across divers projects and environments.
- Experience developing scalable ETL/ELT pipelines.
- Hands-on experience with cloud platforms (AWS, Azure, or GCP).
- Experience working with APIs and web services for data integration.
- Over five (5) years of experience in data modeling, validation, and applying data governance principles to ensure data integrity and compliance.
This position requires a formal degree in the cited discipline area(s) to ensure that candidates have advanced knowledge, analytical skills and professional competencies necessary to perform the duties of the position. The level of degree is commonly recognized as the standard qualification for similar roles in the public and private sector, ensuring that the university remains competitive with industry aligned practices, enhances collaboration with external partners, and supports the delivery of services and programs that meet professional and market-driven expectations.
Preferred Qualifications
- Experience integrating AI/ML workflows into data pipelines.
- Experience with data cataloging and metadata management tools.
- Experience with data security, access control, and compliance frameworks.
- Experience working in an Agile environment with CI/CD tools.
- Excellent communication, documentation, and collaboration skills as evidenced by application materials.
Additional Candidate Instructions
A complete application consists of:
- The University of Kansas online application
- A cover letter that describes how you meet the required and preferred qualifications
- A Resume or CV
- Contact information for three (3) professional references
Incomplete applications will not be considered.
Application review begins Monday, July 28, 2025 and will continue until a qualified applicant has been identified.
Contact Information to Applicants
Prasanna Tadimeti
prasanna@ku.edu
Advertised Salary Range
Starts at $110,000 and is dependent upon experience
Application Review Begins
Monday July 28, 2025
Anticipated Start Date
Monday August 18, 2025
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