Senior Data Engineer - Generative AI

Rochester, MN, United States

Mayo Clinic

View company page

It is an exciting time at Mayo Clinic, as we are building the most trusted generative AI and LLM-based solutions to empower our staff, improve our practice and transform healthcare. To accelerate our generative AI strategy, we are forming a cross functional team of technical experts. This team will be responsible for:

  • Supporting the Generative AI Program’s Request for Application (RFA) Process, its entrants and winners
  • Providing temporary tiger-team efforts to accelerate key initiatives
  • Expanding the organization’s understanding of LLM technology through:
    • Development of best practices, knowledge assets, and code examples to accelerate the efforts of others
    • Execution of technical proofs of concept and exploration
  • Providing consultations, presentations, and sharing of knowledge across Mayo Clinic to technical and non-technical audiences
  • Providing guidance across the Generative AI program workstreams as technical experts

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. May 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.

This is a full time remote position within the United States.  Mayo Clinic will not sponsor or transfer visas for this position including F1 OPT STEM.

This position will accept applications until 5/10/2024.  This deadline may be extended if the necessary candidate pool is not met by this date.

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 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. The ability to navigate linux and windows operating systems is required. Knowledge of workflow scheduling (Apache Airflow Google Composer), Infrastructure as code (Kubernetes, Docker) CI/CD (Jenkins, Github Actions) 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) certification is preferred.

Why Mayo Clinic
Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans – to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic. You’ll thrive in an environment that supports innovation, is committed to ending racism and supporting diversity, equity and inclusion, and provides the resources you need to succeed.
Apply now Apply later
  • Share this job via
  • or

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Agile Airflow AI strategy APIs Big Data BigQuery CI/CD Computer Science D3 DataOps Data pipelines Data visualization DevOps Docker Engineering GCP Generative AI GitHub Google Cloud Java JavaScript Kafka Kubernetes Linux LLMs Machine Learning Mathematics Open Source PHP Pipelines Power BI Python React Research SAS Snowflake Spark SQL SSIS Statistics STEM Streaming Tableau

Perks/benefits: Career development Competitive pay Equity

Region: North America
Country: United States
Job stats:  8  2  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.