IT Senior Data Engineer - Remote

$134,888 - $195,624/Yr

Mayo Clinic - Rochester, MN

Full-time - Mid Level

Remote - Rochester, MN

Hospitals

About the position

As a Senior Data Engineer at Mayo Clinic, you will be at the forefront of transforming healthcare through innovative technology solutions. This role is pivotal in developing and deploying data pipelines, integrations, and transformations that support analytics and machine learning applications. You will work as part of an assigned product team, utilizing various open-source programming languages and commercial software to meet the design functionality for products and programs. Your responsibilities will include maintaining a comprehensive understanding of the organization's current solutions, coding languages, and tools, while applying independent judgment to deliver high-quality results. In this position, you will collaborate closely with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data, conduct exploratory analysis, and transform data to visualize trends. You will also be responsible for building and validating analytical models, translating qualitative and quantitative assessments into actionable insights. Your expertise in designing, building, and installing data systems will be essential in supporting the Department of Data & Analytics technology framework, ensuring that the needs of patients come first in all initiatives. Mayo Clinic is committed to fostering a culture of innovation and high performance, where you will have the opportunity to thrive in an environment that supports diversity, equity, and inclusion. You will be part of a team that is dedicated to delivering the best healthcare solutions, leveraging advanced technologies such as artificial intelligence and machine learning to enhance patient care. This role not only offers the chance to work on cutting-edge projects but also provides a pathway for professional growth and development within a top-ranked healthcare organization.

Responsibilities

• Develop and deploy data pipelines, integrations, and transformations to support analytics and machine learning applications.
• Maintain an understanding of the organization's current solutions, coding languages, and tools.
• Provide consultative services to departments/divisions and leadership committees.
• Partner with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data.
• Conduct exploratory analysis and transform data to help identify and visualize trends.
• Build and validate analytical models and translate assessments into actionable insights.

Requirements

• 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 and a minimum of seven years of professional or research experience.
• Advanced experience in SQL is required.
• Strong experience in scripting languages such as Python, JavaScript, PHP, C++, or Java & API integration is required.
• Experience in hybrid data processing methods (batch and streaming) such as Apache Spark, Hive, Pig, Kafka is required.
• Experience with big data, statistics, and machine learning is required.
• Ability to navigate Linux and Windows operating systems is required.
• Interpersonal skills, time management skills, and demonstrated experience working on cross-functional teams are required.

Nice-to-haves

• Knowledge of workflow scheduling (Apache Airflow, Google Composer) is preferred.
• Experience in DataOps/DevOps and agile methodologies is preferred.
• Experience with hybrid data virtualization such as Denodo is preferred.
• Working knowledge of Tableau, Power BI, SAS, ThoughtSpot, DASH, d3, React, Snowflake, SSIS, and Google Big Query is preferred.
• Google Cloud Platform (GCP) data engineering certification is preferred.

Benefits

• Competitive compensation and comprehensive benefit plans.
• Continuing education and advancement opportunities.
• Support for diversity, equity, and inclusion initiatives.