Breakthrough

The Mayo Clinic Cloud AI team is seeking a highly motivated Data Engineer.  In this role you will build and manage data pipelines as part of a team deploying AI and Machine Learning solutions derived from Mayo Clinic’s AI Innovation Hub.   As a hybrid worker, the role will be primarily remote but candidates will need to be on-site as needed to collaborate with our AI Innovation Hub. Individuals with experience in AI/ML and demonstrated skill building data pipeline solutions on Google Cloud Platform are strongly desired.   

Data Engineer gains access to data across the organization and provides ongoing analysis of the data by monitoring, profiling and analyzing databases. Requires a mix of functional, data and technical skills. The right candidate must be able to understand business requirements, translate them into information needs and implement those requirements using data available. The hire will be responsible for expanding and optimizing data architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems. The Data Engineer will support our software developers, database architects, and data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. 

Core job duties include: 

• Assemble large, complex data sets that meet functional / non-functional business requirements. 
• Strong knowledge of SQL required. Ability to identify sets and subsets of information across multiple joins or unions of tables is preferred in addition to writing and troubleshooting SQL queries for data mining 
• Perform complex data analysis and investigation for customer requests to explain results and to make appropriate recommendations. 
• Strong understanding of data modeling concepts 
• Problem solver with the initiative to think critically to identify improvement opportunities (error detection, error correction, root cause analysis) 
• Understand ETL that will aid in verification and testing of data 
• Build processes supporting data transformation, data structures, metadata, dependency and workload management. 
• A successful history of manipulating, processing and extracting value from large disconnected datasets. 
• Analyze business objectives and develop data solutions to meet customer needs. 
• Demonstrated ability to effectively participate in multiple, concurrent projects 
• Improve and customize current data solutions to meet business functional and non-functional requirements. 
• Research new and existing data sources in order to contribute to new development, improve data management processes, and make recommendations for data quality initiatives. 
• Perform periodic data quality reviews for internal and external data. 
• Ensure timely resolution of queries and data issues. 
• Look for new ways to find and collect data by researching potential new sources of information. 
• Work with data and analytics experts to strive for greater functionality in our data systems.

Bachelor's degree in Computer Science or Engineering from an accredited University or College; OR an Associate’s degree in Computer Science or Engineering from an accredited University or College with 2 years of experience.

Demonstrated ability to analyze and profile data as a means to address various business problems through leveraging advanced data modeling, source system databases, or data mining techniques, is required. May provide consultative services to departments/divisions and committees. Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, and analytical tools and methodologies (e.g. data analysis, data profiling, modeling, etc.) required. Incumbent must have ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. Interpersonal skills and time management skills are required. Requires strong analytical skills and the ability to identify and recommend solutions, advanced computer application skills and a commitment to customer service. Experience with data analysis, quality, and profiling; including data exploration tools including but not limited to Rapid SQL, AQT, Information Analyzer, and Informatics.

Other qualifications for the role include:

• Experience working with large, complex, and heterogeneous data sets (healthcare preferred) 
• Strong knowledge of SQL and Python 
• Experience developing data pipelines and ETL solutions for healthcare related industries. 
• Experience with public cloud computing platforms AWS, Azure, or GCP (preferred) and containerization (Docker) 
• Experience with distributed systems, storage systems, and databases 
• Experience with Agile software development techniques. 
• Knowledge of professional data engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations. Deep hands-on technical expertise, excellent verbal and written communication skills. 
• Adept at working collaboratively within a team environment to accomplish goals 

Preferred qualifications for this position include:

• Ability to use a wide variety of open-source technologies and cloud-based services. 
• Experience with medical imaging systems and data formats (PACS, DICOM) 
• Experience in databases, analytics, big data systems or business intelligence products 
• Experience with building high-performance, highly available and scalable data pipelines and data processing systems. 
• Experience applying solutions in production environments, highlighting an understanding of technology landscapes. 
• Working knowledge of cloud infrastructure and data engineering tools. 
• Familiarity with AI/ML techniques and frameworks. 
• Familiarity with best practices in data engineering, data science, and MLOps communities. 
• Strong curiosity in AI/ML techniques and frameworks, such as deep learning, natural language processing, and Generative AI, and familiarity with tools like TensorFlow or PyTorch 

Authorization to work and remain in the United States, without necessity for Mayo Clinic sponsorship now, or in the future (for example, be a U.S. Citizen, national, or permanent resident, refugee, or asylee). Also, Mayo Clinic does not participate in the F-1 STEM OPT extension program.