Lead Data Engineer

Kent State University

Kent, OH

Job posting number: #7146804

Posted: May 24, 2023

Application Deadline: Open Until Filled

Job Description

Basic Function:

Participate in architectural design, optimization, implementation, and administration of our modern data warehousing environment.  Work with analysts across the university to determine needs and develop data models to support those needs . Optimize data flow and collection from and between multiple complex cloud, on-premises, and hybrid systems. Reports to designated supervisor. 

Additional Basic Function – if applicable:

The Data Management & Analytics team at Kent State University is looking for a Lead Data Engineer to join our team to help us with some exciting data adventures! We are currently working on building a modern analytics solution. Come join us while we build a data lake and data marts that will be used to create a university wide and system agnostic view our data to enable our decision makers to get the data they need and to provide new opportunities in support of predictive analytics and machine learning. Our team is also working with others in the Division of Information Technology to build a data pipeline to enable a consistent, governed way to provide data for application and system integrations.

Examples of Duties:

Duties/essential functions may include, but not be limited to, the following:

Participate in and/or facilitate data discovery sessions with business subject matter experts to translate business needs into enterprise dimensional and relational data models for reporting and analytics.

Design, create and maintain optimal data lake, data mart, data warehouse, and data integration architectures. 

Assemble university-wide complex data sets that meet functional / non-functional business requirements. 

Identify, design, and implement internal data process improvements such as automating manual processes, optimizing data delivery, ensuring data integrity, re-designing infrastructure for greater scalability, etc. 

Build the infrastructure and integrations required for optimal ETL/ELT of data from a wide variety of complex cloud, hybrid, and on-premises data sources. 

Participate in development and implementation of data lifecycle of the modern data warehousing environment. 

Lead and educate and mentor team members on best practices. Perform code and model design reviews.

Provide oversight / guidance related to data issues needing technical expertise.

Perform related duties as assigned.


Communicate effectively with technical and non-technical users.

Maintain cooperative working relationships.

Manage time and effectively balance multiple evolving priorities.

Work effectively with very limited oversight.

Establish estimates and timelines for specific applications/projects and take direct accountability for results.

Establish focused, measurable goals for self and others.

Additional Examples of Duties – if applicable:

Minimum Qualifications:

Bachelor’s degree in computer science, information technology or a related field of study. Minimum of seven years progressive experience in the following: 

Analyzing and translating business needs into long-term solution data models.
Experience data modeling principles/methods to design dimensional data models from the ground up.
Working with relational databases, as well as working familiarity with a variety of databases.
Advanced logical data model design, data warehouse design, and data integration.
Performing root cause analysis to perform troubleshooting on data flows through complex systems.
Analyzing internal and external data and processes for a business to build models to answer specific business questions.
Building processes for data transformation.
Developing and maintaining system documentation, metadata, data standards, and data quality metrics for data management systems.
Experience writing advanced SQL.

Knowledge Of:

Advanced logical data design, data warehouse design, and data integration as well as the management of web content or other unstructured data
Common software application packages and tools for performance monitoring and issues tracking
Testing practices, application debugging, and troubleshooting procedures
Software development life cycle, structured programming, object-oriented design and development techniques, and change management
Managing the development and maintenance of system documentation, metadata, data standards, and data quality metrics for the data management system
Advanced working knowledge of SQL

Skill In:

Time management with the ability to set priorities to coordinate multiple assignments with fluctuating and time-sensitive deadlines
Written and interpersonal communication, with the ability to present complex technical information in a clear and concise manner to a variety of audiences

Ability To:

Foster positive and professional working relationships; effectively handle interpersonal interactions at all levels; and respond appropriately to conflicts and problems
Work with technical and non-technical staff to identify user needs and translate them into technology-based solutions
Keep abreast of industry trends

Preferred Qualifications – if applicable:

Experience working in a higher education institution.
Experience facilitating data discovery sessions to gather requirements needed to build data models.
Experience building solutions to support analytics, machine learning, and data science.
Experience with datalake and data warehouse technologies.
Experience with data analytics tools.
Experience developing solutions that are incorporated into all aspects of an organization’s data services to achieve data governance and data quality best practices.

Asterisk (*) indicates knowledge, skills, abilities which require assessments

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