Senior Data Engineer - Digital Pathology (Hybrid)

Mayo Clinic•Rochester, MN

3d•$141,024 - $204,526•Hybrid

About The Position

Mayo Clinic is a top-ranked healthcare provider dedicated to putting patient needs first. They invest in competitive compensation and comprehensive benefit plans for their employees, offering continuing education and advancement opportunities for long-term career success. This Senior Data Engineer role is part of the Digital Pathology team and is a hybrid position, requiring the employee to be located within 100 miles of the Mayo Clinic campus in Rochester, MN for quarterly on-site expectations. This position is not eligible for visa sponsorship or F-1 STEM OPT extension.

Requirements

Bachelor's degree in a relevant field (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 and a minimum of seven years of professional or research experience in data visualization, data engineering, analytical modeling techniques.
Ability to manage a varied workload of projects with multiple priorities.
Ability to stay current on healthcare trends and enterprise changes.
Interpersonal skills, time management skills, and demonstrated experience working on cross-functional teams.
Strong analytical skills and the ability to identify and recommend solutions.
Commitment to customer service.
Excellent verbal and written communication skills.
Attention to detail.
High capacity for learning and problem resolution.
Advanced experience in SQL.
Strong Experience in scripting languages such as Python, JavaScript, PHP, C++ or Java & API integration.
Experience in hybrid data processing methods (batch and streaming) such as Apache Spark, Hive, Pig, Kafka.
Experience with big data, statistics, and machine learning.
Ability to navigate Linux and Windows operating systems.

Nice To Haves

In-depth business or practice knowledge.
Knowledge of workflow scheduling (Apache Airflow Google Composer).
Knowledge of Infrastructure as code (Kubernetes, Docker).
Knowledge of CI/CD (Jenkins, Github Actions).
Experience in DataOps/DevOps and agile methodologies.
Experience with hybrid data virtualization such as Denodo.
Working knowledge of Tableau, Power BI, SAS, ThoughtSpot, DASH, d3, React, Snowflake, SSIS, and Google Big Query.
Google Cloud Platform (GCP) certification.

Responsibilities

Develops and deploys data pipelines, integrations, and transformations to support analytics and machine learning applications and solutions.
Works as part of an assigned product team using various open-source programming languages and vended software.
Maintains an understanding of the organization's current solutions, coding languages, and tools.
Applies independent judgment regularly.
May provide consultative services to departments/divisions and leadership committees.
Demonstrates experience in designing, building, and installing data systems and their application to the Department of Data & Analytics technology framework.
Partners with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data.
Conducts exploratory analysis, pipeline, and transform data to help identify and visualize trends.
Builds and validates analytical models.
Translates qualitative and quantitative assessments into actionable insights.