Principal Data Engineer

Job-:
Data Science

Location:

Rochester, MN, United States

Schedule:

Full time Posted:
Closes:
Hours / Pay Period: 80

Benefits Eligible:
Yes Remote worker: 100% remote work Compensation Detail: $148,100 - $214,700 / year Weekend

Schedule:

Not Applicable Union Job:
No

Area of Interest 1:
Mayo Clinic Platform Marketing Category 1:
Business International Assignment:
No

Overtime Rule:
Salaried employee who does not receive overtime pay Principal Data Engineers at Mayo Clinic are expected to be subject matter experts in building ETL pipelines, working with heterogenous data using different technologies, and database design and optimizations. The data they work with are required to support a different analyses and applications that serve both internal and external partners. As the position requires strong data, technical, and functional skills, the right candidate must be able to understand business requirements, translate them into information needs, and implement those requirements using available data.

The hire will be responsible for creating new data architecture, optimizing existing databases, designing data collection and flows for cross functional teams. The ideal candidate is an data engineer who has extensive experience working with clinical data and collaborating across diverse teams to ensure the data provided is accurate, the data pipelines reliable, and the resulting databases are fit for a variety of purposes.

The Principal Data Engineer will work with informaticists, clinicians, software engineers, and data scientists to serve as a subject matter expert in data engineering best practices and will ensure optimal data delivery architecture is consistent throughout ongoing projects. The position will also be responsible for the management of data related projects and oversee the tasks of other team members when relevant.

Core job duties:

Expert in data modeling concepts,Responsible for designing, implementing, documenting and testing databases containing clinical data.

Leverage SQL, Python and other programming languages

Assemble large, complex data sets that meet functional / non-functional business requirements.

Build ETL pipelines from varying data sources and technologies using cloud technologies such as Google Cloud or Microsoft Azure and implemented with Apache Airflow or similar products

Problem solving with the initiative to think critically to identify improvement opportunities.

Provide direction on best practices for data transformation, structure, and workflows.

Ability to effectively participate in multiple, concurrent projects

Research new and existing data sources in order to contribute to new development, improve data management processes, and make recommendations for data quality initiatives.

Perform periodic data quality reviews for internal and external data.

QualificationsA Master's degree in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative and a minimum of five years of professional or research experience in data science
The successful candidate will need to have both technical and business background/experience along with strong leadership skills. Good written and oral communication skills are required. Deep expertise in the use of scientific computing and data management packages. Ability to prioritize, organize, and delegate various tasks on projects. Demonstrated initiative in administration, education (seminars, training), software development, and technical reports. Demonstrated success in project management and communication skills.

Demonstrated ability to develop predictive and prescriptive models on large-scale datasets to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques. Demonstrated ability to provide consultative services at an institutional or enterprise level to departments/divisions and committees from any Mayo entity requesting assistance is preferred. Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, project management methods, and analytical tools and methodologies (e.g. machine learning, statistical packages, modeling, etc.)

required. Incumbent must have ability to independently manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. Excellent interpersonal skills to include presentation, negotiation,…