Breakthrough

We are seeking a Senior Data Engineer to join our growing Research Data and Digital Transformation team. In this role, you will play a critical part in building scalable, secure, and high-performance data platforms that support advanced research across biomedical, clinical, and translational domains.
You will work closely with data scientists, informaticians, software engineers, and researchers to design robust data infrastructure that enables real-time insights and longitudinal studies across Mayo Clinic’s vast research ecosystem.

Key Responsibilities
•    Design, build, and maintain cloud-native data pipelines and infrastructure using Google Cloud Platform (GCP)services such as BigQuery, Cloud Dataflow, Cloud Storage, and Pub/Sub.
•    Integrate and normalize data from diverse sources including EHR systems, genomic data, clinical trials, imaging, and external data networks.
•    Optimize data modeling, partitioning, and querying strategies to support advanced analytics, AI/ML, and research workloads.
•    Collaborate with cross-functional teams to define data strategy, governance, and quality assurance processes.
•    Implement secure, compliant, and auditable data handling practices in accordance with institutional and regulatory standards.
•    Mentor junior engineers and contribute to a culture of technical excellence and innovation.

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.

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.

Additional Preferred Qualifications:

• Master’s degree in Data Engineering, Computer Science, Bioinformatics, or related discipline.
• Experience working with healthcare or research data (EHRs, HL7/FHIR, genomics).
• Familiarity with regulatory requirements related to health data (HIPAA, IRB, etc.).
• Exposure to AI/ML workflows and tools such as Vertex AI, Jupyter, or TensorFlow.