Senior Data Engineer
The Ohio State UniversityAbout the role
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Job Title:
Senior Data EngineerDepartment:
OCIO | Enterprise ApplicationsThe Data and Analytics Team within the Office of Technology and Digital Innovation (OTDI) at The Ohio State University manages the enterprise data reporting, analytics, and governance environments that support leaders, decision-makers, and data analysts/scientists across campus. Our vision is to enable a culture of data enablement and thought leadership through accurate, accessible information and innovative analytics.
This Senior Data Engineer position will help realize the design and build of ETL/ELT and other data integration movement processes for the Reporting and Analytics Environment; among other systems we manage within the department. Our current system implementations include cloud-based analytics solutions (IAAS PAAS SAAS) and interactions with internal OSU systems across the enterprise.
The technologies we use daily focus on modern data analytics architectures backed by big data tools. This role will utilize data integration methodologies and design practices to move data from source systems into secure and governed data analytics and/or data hub environment. The work also focuses on making this data available to analysts, users, and systems.
The Senior Data Engineer will be responsible for engaging with other data engineers within the team as well as collaborating with OTDI Infrastructure colleagues and specialists in designing and implementing integrations from multiple systems into the team's data environments. It is expected that this resource will work to obtain and refine data requirements, build data integration flows, partner with data and visualization analysts on query optimization and tuning, and confer with data governance resources on metadata requirements.
Also, will provide production support duties for the systems we manage; this role will respond to help desk issues related to our systems, be responsible for monitoring the production support queue, and respond to data flow failures in a timely manner. This includes participating in rotating off-hours and weekend on-call/pager duty.
Required Education and Experience:
Bachelor's Degree or equivalent experience. 4 years of relevant experience related to
· Demonstrated deep understanding of SQL and hands-on experience implementing ETL (or ELT) best practices at scale.
· 3 to 5 years using Python, Java, Scala, or other programming languages for data processing (Python preferred)
· Experience in working with business and process analysts in gathering requirements as well as in collaborative data movement design and data governance.
· Familiar with modern data analytics technologies and techniques, such as cloud-based
· analytics environments (AWS, Azure, GCP) serverless coding streaming and micro-batch data loads code automation continuous development delivery and integration
· Experience with web services/APIs (REST, SOAP), S/FTP, and data interchange formats (JSON, XML, CSV)
· Strong interpersonal skills, including excellent customer service and relationship management skills.
· Detail-oriented and desire to continually keep up with advancements in data engineering practices.
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