Breakthrough

Works with MCP Director of Data Asset Management on executing MCP data roadmap. Develops and deploys data pipelines and data warehouses to support MCP Data & Analytics operations. Uses various open-source programming languages, Google Cloud technologies, machine learning models, and vended software to meet data needs of MCP products. The position requires maintaining an understanding of the Mayo's data policies, enterprise data warehouse, and regularly requires the application of independent judgment. Demonstrated experience in designing, building, and installing data systems and how they are applied to support Mayo Clinic Platform products is required. Builds data pipelines to handle large volumes of clinical data including EHR data, DICOM data, and Genomic data..

A Bachelor's degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of five years of professional or research experience in data visualization, data engineering, analytical modeling techniques; OR an Associate's degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of seven years of professional or research experience in data visualization, data engineering, analytical modeling techniques. In-depth business or practice knowledge will also be considered.

Incumbent must have the ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. Interpersonal skills, time management skills, and demonstrated experience working on cross functional teams are required. Requires strong analytical skills and the ability to identify and recommend solutions and a commitment to customer service. The position requires excellent verbal and written communication skills, attention to detail, and a high capacity for learning and problem resolution. Advanced experience in SQL is required. Strong Experience in programming languages such as Python, JavaScript, PHP, C++ or Java & API integration is required. Experience with data warehouse technologies such as BigQuery, DB2 and RDBMS is required. Experience in hybrid data processing methods (batch and streaming) such as Apache Spark, GC Dataflow and GC Data Fusion is required. Experience with big data, statistics, and machine learning is required. The ability to navigate linux and windows operating systems is required. Knowledge of workflow scheduling (Apache Airflow Google Composer), Infrastructure as code (Terraform, Kubernetes, Docker), CI/CD (Jenkins, Github Actions) is preferred. Experience agile methodologies is preferred. Working knowledge of Tableau, Power BI, SAS, and SSIS is preferred.