Principal Data Engineer

Mayo Clinic•Rochester, MN

About The Position

Principal Data Engineers at Mayo Clinic are subject matter experts in building ETL pipelines, working with heterogeneous data across different technologies, and designing and optimizing databases. The data supports analyses and applications for internal and external partners. The role translates business requirements into information needs and implements them using available data. The Principal Data Engineer creates data architectures, optimizes databases, and designs data collection and flows for cross-functional teams. The successful candidate brings extensive experience with clinical data and collaborates with informaticists, clinicians, software engineers, and data scientists to ensure accurate data, reliable pipelines, and databases suited to varied purposes. The role provides subject-matter expertise in data engineering best practices and helps ensure consistent, effective data-delivery architecture across projects. It also includes managing data-related projects and overseeing other team members’ tasks when relevant. The role involves designing, implementing, documenting, and testing clinical-data databases; assembling complex data sets; building ETL pipelines from varied sources using cloud technologies and workflow tools; researching data sources; and reviewing data quality. It also calls for technical and business acumen, leadership, project-management skills, and the ability to independently manage competing priorities while staying current on healthcare trends and enterprise changes.

Requirements

Master’s degree in a relevant field such as engineering, mathematics, computer science, health science, or another analytical or quantitative field, and at least five years of professional or research experience in data science.
Technical and business background or experience, along with strong leadership skills.
Strong written and oral communication skills, including presentation, negotiation, persuasion, and written communications.
Deep expertise in scientific computing and data-management packages.
Ability to prioritize, organize, and delegate project tasks.
Demonstrated success in project management and communication.
Demonstrated ability to develop predictive and prescriptive models on large-scale data sets using advanced statistical modeling, machine learning, or data-mining techniques.
Demonstrated application of problem-solving methodologies, planning techniques, continuous-improvement methods, project-management methods, and analytical tools and methodologies.
Ability to independently manage a varied workload with multiple priorities and stay current on healthcare trends and enterprise changes.
Excellent analytical and consulting skills; ability to identify and recommend solutions; advanced computer application skills; and commitment to customer service.
Experience with data modeling and data exploration tools.
Demonstrated ability to analyze and profile data using advanced data modeling, source-system databases, or data-mining techniques.
Experience with data analysis, data quality, and profiling.
Proficiency in SQL and one other programming language commonly used in data engineering, such as Python or Scala.
Experience working with one or more cloud technologies: Amazon Web Services, Google Cloud, or Microsoft Azure.

Nice To Haves

Demonstrated ability to provide consultative services at an institutional or enterprise level to departments, divisions, and committees across Mayo entities.
Advanced degree (Ph.D. or M.Sc.) in computer science, engineering, or a quantitative field from an accredited university or college, with five or more years of experience; alternatively, a bachelor’s degree in computer science, engineering, or a quantitative field from an accredited university or college, with ten or more years of experience.

Responsibilities

Design, implement, document, and test databases containing clinical data.
Create data architecture and optimize existing databases.
Design data collection and data flows for cross-functional teams.
Build ETL pipelines from varied data sources and technologies, using cloud technologies and Apache Airflow or similar products.
Assemble large, complex data sets that meet functional and non-functional business requirements.
Provide direction on best practices for data transformation, structure, and workflows.
Research new and existing data sources to support development, improve data management processes, and recommend data-quality initiatives.
Conduct periodic data-quality reviews for internal and external data.
Manage data-related projects and oversee other team members’ tasks when relevant.
Participate effectively in multiple concurrent projects and independently manage a varied workload with competing priorities.
Apply problem-solving, planning, continuous-improvement, project-management, and analytical methodologies to business problems.
Develop predictive and prescriptive models on large-scale data sets using statistical modeling, machine learning, or data-mining techniques.
Analyze and profile data to address business problems using data modeling, source-system databases, or data-mining techniques.
Provide consultative services to departments, divisions, and committees across Mayo entities when requested.
Stay current on healthcare trends and enterprise changes.
Demonstrate initiative in administration, education such as seminars and training, software development, and technical reports.