Principal Data Engineer - AI Program

Mayo Clinic•Rochester, MN

About The Position

Develops and deploys data pipelines, integrations and transformations to support analytics and machine learning applications and solutions as part of an assigned product team using various open-source programming languages and vended software to meet the desired design functionality for products and programs. The position requires maintaining an understanding of the organization's current solutions, coding languages, tools, and regularly requires the application of independent judgment. Will provide consultative services to departments/divisions and leadership committees. Demonstrated experience in designing, building, and installing data systems and how they are applied to the Department of Data & Analytics technology framework is required. Candidate will partner with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data, conduct exploratory analysis, pipeline and transform data to help identify and visualize trends, build and validate analytical models, and translate qualitative and quantitative assessments into actionable insights.

Requirements

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 seven 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 nine years of professional or research experience in data visualization, data engineering, analytical modeling techniques.
In-depth business or practice knowledge.
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.
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.
Advanced 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.
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.

Nice To Haves

Experience in hybrid data virtualization such as Denodo.
Working knowledge of Tableau, Power BI, SAS, ThoughtSpot, DASH, d3, React, Snowflake, SSIS, and Google Big Query.

Responsibilities

Develops and deploys data pipelines, integrations and transformations to support analytics and machine learning applications and solutions.
Maintain an understanding of the organization's current solutions, coding languages, tools.
Provide consultative services to departments/divisions and leadership committees.
Design, build, and install data systems and apply them to the Department of Data & Analytics technology framework.
Partner with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data.
Conduct exploratory analysis, pipeline and transform data to help identify and visualize trends.
Build and validate analytical models.
Translate qualitative and quantitative assessments into actionable insights.

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