Job description

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. A 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, persuasion, and written communications skills are required. Exceptional time management is required. In addition, requires excellent analytical skills, consulting skills, ability to identify and recommend solutions, advanced computer application skills and a commitment to customer service. Experience with data modeling and date exploration tools. Preferred Experience Advanced degree (Ph.D, M.Sc) in Computer Science, Engineering or quantitative field from an accredited University or College with 5+ years of experience; OR a Bachelor's degree in Computer Science, Engineering, or quantitative field from an accredited University or College with 10+ years of experience. Requirements • Demonstrated ability to analyze and profile data as a means to address various business problems through leveraging advanced data modeling, source system databases, or data mining techniques. • Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, and analytical tools and methodologies (e.g. data analysis, data profiling, modeling, etc.). • Incumbent must have ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. • Interpersonal skills and time management skills are required. • Strong analytical skills and the ability to identify and recommend solutions, advanced computer application skills and a commitment to customer service. • Experience with data analysis, quality, and profiling. • Proficient in SQL and one other programming language commonly used in data engineering (Python, Scala, etc). • Experience in working with one or more cloud technologies: Amazon Web Services, Google Cloud Projects, or Microsoft Azure

Requirements

Must-haves

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.
Demonstrated ability to analyze and profile data as a means to address various business problems through leveraging advanced data modeling, source system databases, or data mining techniques.
Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, and analytical tools and methodologies (e.g. data analysis, data profiling, modeling, etc.).
Incumbent must have ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes.
Interpersonal skills and time management skills are required.
Strong analytical skills and the ability to identify and recommend solutions, advanced computer application skills and a commitment to customer service.
Experience with data analysis, quality, and profiling.
Proficient in SQL and one other programming language commonly used in data engineering (Python, Scala, etc).
Experience in working with one or more cloud technologies: Amazon Web Services, Google Cloud Projects, or Microsoft Azure

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlpythonazuremachine learning

Platform: oracle-cloud
Effort: medium

Benefits

Benefits detected in the listing.

Vision