Data Engineer II

Position Title:

Data Engineer II

Department:

IT Care Delivery Applications

Job Description:

The Data Engineer II designs, develops and delivers data pipelines and value-added data assets across the OU Health data ecosystem, leveraging a variety of data engineering and data warehousing methodologies and disciplines. The Data Engineer II works closely with data scientists, business intelligence developers, and other colleagues to build or enhance robust systems. The Data Engineer II mentors junior ETS colleagues and emphasizes agility, partnership, and cross functional teamwork.

Essential Responsibilities

Responsibilities listed in this section are core to the position. Inability to perform these responsibilities with or without an accommodation may result in disqualification from the position.

• Incorporate new business and system data into the Data Warehouse while maintaining enterprise best practices and adhering to data governance standards.
• Apply business rules to our data as we migrate from source to target using Informatica or scripting language. Validate data to ensure quality
• Collaborate with colleagues across the enterprise to scope requests.
• Extract data from various data sources, validate results, create relevant data visualizations, and share with requester.
• Develop dashboards and automate refreshes as appropriate.
• Manage initiatives & projects of average complexity and risk.
• Provide leadership to assigned delivery teams.
• Provide input to prioritized roadmaps, develop work estimates, and ensure successful delivery to support strategic planning and initiatives, improve organizational performance, and advance progress towards OU Health goals.
• Work closely with different application and operational teams to understand business needs and align data engineering initiatives accordingly.
• Investigates highly technical issues identified from the use of multiple data sources and determines the appropriate use of action for the organization.
• Guide, mentor and train Data Engineer I and Business Intelligence Developers on technical skills and best practices.
• Ability to work independently and within teams.
• Ability to develop and advise on data asset use to provide solutions to organizational needs.

General Responsibilities

• Performs other duties as assigned.

Minimum Qualifications

Education Requirements: Bachelor's Degree required.

Experience Requirements:  3-5 years in analytics (Business Intelligence, Data Engineering, Data Science, etc.) including 2 years in a Data Engineering or Data Warehousing role required. Cloud or healthcare experience preferred.

License/Certification/Registration Requirements: 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

• Additional epic classes as requested to support evolving business needs

Knowledge/Skills/Abilities Required:

• Strong 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.

• Advanced SQL and data manipulation skills,

• Exposure to big data tools: dbt, SnowPark, Spark, Kafka, etc.

• Experience with relational SQL and NoSQL databases, including Snowflake, MS SQL Server, and Postrgres

• Exposure to data integration tools: Fivetran, Matillion, SSIS, dbt, SnowSQL.

• Exposure to stream-processing systems: IBM Streams, Flume, Storm, Spark-Streaming, etc.

• Exposure to consuming and building APIs

• Exposure to object-oriented/object function programming languages: Python, Java, C++, Scala, etc.

• Exposure to statistical data analysis tools: R, SAS, SPSS, etc.

• Experience with visual analytics tools: QlikView, Tableau, Power BI etc.<