Senior Data Engineer

Kent State • Kent, OH

9d • $77,158 - $91,853 • Onsite

About The Position

The Data Management & Analytics team at Kent State University is looking for a Senior Data Engineer to join us as we continue modernizing the university's analytics and integration platforms. Our team develops and supports the data platforms that power reporting, analytics, decision making, and enterprise integrations across the university. In this role, you'll work across both our analytics and data engineering initiatives, helping design and build scalable data pipelines, data models, and integration solutions that connect information from systems throughout the institution. This is an opportunity to work on a wide variety of projects, from enabling university-wide analytics and reporting to supporting critical enterprise integrations and data services. If you enjoy solving complex data challenges, working with modern technologies, and helping shape how data is managed and delivered at scale, we'd love to hear from you.

Requirements

• Bachelor’s degree in computer science, information technology or a related field of study.
• Minimum of five years progressive experience in 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.
• Communicate effectively, orally and in writing, 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.
• 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
• Time management with the ability to set priorities to coordinate multiple assignments with fluctuating and time-sensitive deadlines
• Written and verbal communication, with the ability to present complex technical information in a clear and concise manner to a variety of audiences
• 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

Nice To Haves

• Experience working in a higher education institution.
• 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.

Responsibilities

• Create and maintain optimal data lake, data mart, data warehouse, and data integration architectures.
• Assemble large, 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 cloud, hybrid, and on-premises data sources.
• Participate in development and implementation of data lifecycle of the modern data warehousing environment.
• Coach and perform code reviews for other team members and data professionals across the university.
• Perform related duties as assigned.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior