Data Engineer III

OU Health • WFH State of Oklahoma, OK

22h • Remote

About The Position

This position may be performed remotely from the following locations within the United States of America: Arkansas, Kansas, Missouri, Oklahoma, and Texas. Please only apply if you live and work full-time in one of the states listed above or plan to relocate to one of these states before starting your employment with OU Health. The Data Engineer III leads and serves as the subject matter expert in the design, development and delivery of data pipelines and value-added data assets across the OU Health data ecosystem, leveraging a variety of data warehousing methodologies and disciplines. The Data Engineer III primarily designs, builds, and maintains these data assets. Emphasizing agility, partnership, and cross-functional teamwork, the Data Engineer III executes initiatives throughout the product lifecycle. The Data Engineer III works closely with Data Scientists, Business Intelligence Developers and other colleagues to build or enhance robust data systems. Initiatives will often be of significant complexity and risk. The Data Engineer III serves as a technical guide and mentor to the ETS department.

Requirements

• Bachelor's Degree required.
• 5 or more years in analytics (Business Intelligence, Data Engineering, Data Science, etc.) required.
• Epic certification/accreditation required within 6 months of hire or within 3 months of class completion including: Cogito Fundamentals, Clarity Data Model, Caboodle Data Model, Access Data Model, Revenue Data Model, Clinical Data Model, Caboodle Development
• Expert level analytic skills related to working with structured and unstructured datasets.
• Must possess critical thinking and creative problem-solving skills along with the ability to communicate well with stakeholders throughout the organization.
• Effective communication, project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Working knowledge of stream processing and highly scalable data stores.
• Previous experience manipulating, processing, and extracting value from large, disconnected datasets.
• Expert level SQL and data manipulation skills
• Experience with relational SQL and NoSQL databases, including Snowflake, MS SQL Server, and Postrgres
• Experience with integration tools: Fivetran, Matillion, SSIS, dbt, SnowSQL.
• Exposure to consuming and building APIs
• Experience with statistical data analysis tools: R, SAS, SPSS, etc.
• Experience with visual analytics tools: QlikView, Tableau, Power BI etc.
• Familiarity to Agile methodology for development
• Familiarity with electronic health records and financial systems. i.e., Epic Systems, Workday, Strata etc.
• Ability to work independently and within teams.
• Ability to develop and advise on data asset use to provide solutions to organizational needs.

Nice To Haves

• Additional epic classes as requested to support evolving business needs
• Guide, mentor and train Data Engineering team, Data Scientist and Business Intelligence Developers on technical skills and best practices.
• Exposure to big data tools: dbt, SnowPark, Spark, Kafka, etc.
• Exposure to stream-processing systems: IBM Streams, Flume, Storm, Spark-Streaming, etc.
• Exposure to object-oriented/object function programming languages: Python, Java, C++, Scala, etc.

Responsibilities

• Leverage subject matter expertise with a variety of data engineering, DataOps, and data warehousing methodologies, techniques, tools, and platforms to transform large quantities of data from multiple sources.
• Design, create, test, deploy and maintain data pipelines that deliver curated, value-added data assets such as data marts and other purpose-built data stores.
• Ensure data pipelines are optimized, highly reliable, and contain low technical debt.
• Design, build, and maintain the tools and infrastructure needed to handle large datasets.
• Enforce data governance policies including data quality, validation, lineage, metadata management, and adherence to healthcare regulations
• Develop and implement comprehensive data quality frameworks, addressing issues such as data accuracy, completeness, and consistency
• Work closely with different application and operational teams to understand business needs and align data engineering initiatives accordingly.
• Guide, mentor, quality review and train Data Engineering team and ETS department on technical skills and best practices.
• Performs other duties as assigned.

Benefits

• PTO
• 401(k)
• medical and dental plans

What This Job Offers

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