Data Engineer II

Cincinnati Children's

1d•Remote

About The Position

The Data Engineer II designs, builds, tests, and manages simple to moderately complex data pipelines that move data from source systems through integration to production consumption by business and data analysts, data scientists, and other analytics users. The role ensures compliance with data governance and security requirements, follows development best practices, supports ETL changes and upgrades, and develops solutions that meet research, regulatory, benchmarking, and process-improvement needs without interfering with transactional systems. The position develops and documents data models and extraction processes, improves data preparation and integration through automation, and works with customers, analytics teams, platform engineers, database administrators, and vendors to deliver scalable, efficient solutions. It also provides second-level support and incident resolution, monitors service-level agreements, maintains support documentation, and contributes to customer satisfaction and change management. The Data Engineer II executes project work, communicates progress through departmental tools, participates in project meetings, and may serve as technical lead for moderately complex projects. The role takes 24-hour call on a staff rotation and is based remotely, with a day shift schedule of 40 hours per week.

Requirements

Bachelor’s degree in computer science, statistics, applied mathematics, data management, information systems, information science, or a related quantitative field.
At least 2 years of work experience in a related job discipline.
Proficiency in one or more data management practices and architectures, such as data modeling, data warehousing, data lakes, or data hubs, and foundational understanding of the others.
Proficiency with SQL, object-oriented or object-function scripting, and DevOps principles.

Nice To Haves

Experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental or multi-departmental data management and analytics initiative.

Responsibilities

Design, build, test, and manage simple to moderately complex data pipelines from acquisition through integration to production consumption.
Ensure data pipelines comply with data governance and data security requirements, and partner with platform engineers and database administrators.
Follow development best practices for agile updates from development to production and back; make changes to ETL processes and support upgrades and testing.
Pursue additional options for extracting and analyzing data from the Epic source system to support research, regulatory, and collaborative initiatives.
Develop solutions for benchmarking and process-improvement data requests, including moderately complex solutions that avoid interference with transactional systems.
Develop and implement simple to moderately complex data models in support of CCHMC strategies.
Work with customers and report and analytics development groups to promote scalable and efficient solutions.
Document data models and extraction processes so team members and customers can understand design objectives.
Use modern tools, techniques, and architectures to automate repeatable data preparation and integration tasks and reduce manual, error-prone processes.
Refine existing solutions and apply best practices to reports, database structures, and extraction techniques.
Work with vendors as needed to support and enhance CCHMC investments and requests.
Address reporting requests requiring complex solutions or deeper knowledge of source-system data models.
Apply data management practices and architectures, including data modeling, data warehousing, data lakes, and data hubs; use SQL, object-oriented or object-function scripting, and DevOps principles.
Build understanding of CCHMC clinical, business, and research processes; obtain Epic certifications as appropriate and develop skills through continuing education.
Provide end-user support, monitor service-level agreements for incident management, and collaborate with other teams on customer-centered support.
Promote change-management policies and procedures, provide timely customer follow-up, and escalate support issues with urgency.
Collaborate with stakeholders, particularly data science teams and business data analysts, to refine data requirements and data consumption needs.
Provide second-level incident and problem resolution, contribute to customer-satisfaction improvements, and maintain and refine support documentation.
Take 24-hour call on a staff rotation.
Execute project tasks urgently and to a high standard, communicate status using departmental project management tools, and follow time-tracking and other project management requirements.
Participate in project meetings and stand-ups; serve as technical lead for moderately complex projects and collaborate with project managers on scope, risk, and budget management.
Lead project meetings and workgroups.