Senior Data Engineer - Hybrid
About The Position
The Senior Data Engineer will join Mayo Clinic’s Research Data Atlas team to build and advance its enterprise research data platform. Atlas centralizes, catalogs, integrates, harmonizes, and delivers complex research data so investigators can discover, access, combine, and analyze information across studies and data domains. It supports genomic and other omics data, biospecimens, clinical and phenotypic information, laboratory data, imaging, and other research data for translational research, precision medicine, artificial intelligence, and advanced analytics. The role designs, builds, and supports scalable data products, pipelines, integrations, and services for complex biomedical research use cases. It works with large-scale genomic and multimodal datasets and translates investigator and scientific requirements into technically sound and scientifically appropriate solutions. Work includes data ingestion and transformation, integration across clinical and research systems, harmonization of disparate data structures and standards, metadata and provenance maintenance, data-quality validation, and enabling secure, governed access to research datasets. Substantial research informatics experience is required, including genomic and/or other omics data, next-generation sequencing concepts, common genomic data formats, genomic variants and annotations, normalization and harmonization, study and sample metadata, provenance, scientific data quality, and human-subjects research data governance. The engineer works independently with bioinformaticians, computational scientists, investigators, laboratory personnel, and other research stakeholders. The position uses Google Cloud Platform and technologies including BigQuery, Cloud Storage, Dataflow, Batch, Pub/Sub, and related cloud-native services. Experience with modern AI-assisted and agentic development tools such as Claude Code, OpenAI Codex, or comparable platforms is required for software development, data engineering, testing, troubleshooting, documentation, and code quality. The engineer develops and deploys data pipelines, integrations, and transformations to support analytics and machine learning applications as part of an assigned product team. The role partners with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data, conduct exploratory analysis, pipeline and transform data, build and validate analytical models, and translate qualitative and quantitative assessments into actionable insights. This is a hybrid position. The employee must be located within 100 miles of a Mayo Clinic campus for occasional on-site expectations based on business needs.
Requirements
- A relevant bachelor's degree and at least five years of professional or research experience in data visualization, data engineering, or analytical modeling techniques; or a relevant associate’s degree and at least seven years of such experience. In-depth business or practice knowledge will also be considered.
- Substantial research informatics experience, including experience with genomic and/or other omics data.
- Knowledge and experience with next-generation sequencing concepts, common genomic data formats, genomic variants and annotations, normalization and harmonization, research-study and sample metadata, data provenance, scientific data quality, and human-subjects research data governance.
- Demonstrated experience designing, building, and installing data systems.
- Advanced experience in SQL.
- Strong experience with scripting languages such as Python, JavaScript, PHP, C++, or Java, and API integration.
- Experience with hybrid data processing methods, including batch and streaming, such as Apache Spark, Hive, Pig, or Kafka.
- Experience with big data, statistics, and machine learning.
- Ability to navigate Linux and Windows operating systems.
- Required experience using Google Cloud Platform and cloud technologies such as BigQuery, Cloud Storage, Dataflow, Batch, Pub/Sub, and related cloud-native services.
- Experience using modern AI-assisted and agentic development tools such as Claude Code, OpenAI Codex, or comparable platforms.
- Ability to manage multiple project priorities, strong analytical and problem-solving skills, interpersonal and time-management skills, cross-functional teamwork experience, customer-service commitment, excellent verbal and written communication, attention to detail, and capacity for learning and problem resolution.
- Must be located within 100 miles of a Mayo Clinic campus for occasional on-site expectations.
- The position is not eligible for sponsorship or visa transfer; Mayo Clinic does not participate in the F-1 STEM OPT extension program.
Nice To Haves
- Knowledge of workflow scheduling, such as Apache Airflow or Google Composer.
- Knowledge of infrastructure as code, including Kubernetes or Docker.
- Knowledge of CI/CD tools such as Jenkins or GitHub Actions.
- Experience in DataOps/DevOps and agile methodologies.
- Experience with hybrid data virtualization such as Denodo.
- Working knowledge of Tableau, Power BI, SAS, ThoughtSpot, DASH, d3, React, Snowflake, SSIS, and Google BigQuery.
- Google Cloud Platform certification.
Responsibilities
- Design, build, and support scalable data products, pipelines, integrations, and services for complex biomedical research use cases.
- Ingest and transform research data and integrate information across clinical and research systems.
- Harmonize disparate data structures and standards, maintain metadata and provenance, validate data quality, and enable secure, governed access to research datasets.
- Translate investigator and scientific requirements into technically sound and scientifically appropriate solutions.
- Work with large-scale genomic and multimodal datasets and collaborate independently with bioinformaticians, computational scientists, investigators, laboratory personnel, and other research stakeholders.
- Develop and deploy data pipelines, integrations, and transformations for analytics and machine learning applications as part of an assigned product team.
- Partner with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data, conduct exploratory analysis, and pipeline and transform data.
- Build and validate analytical models and translate qualitative and quantitative assessments into actionable insights.
- Use AI-assisted and agentic development tools to support software development, data engineering, testing, troubleshooting, documentation, and code quality.
- Manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes.
Benefits
- Competitive compensation and comprehensive benefit plans.
- Medical plan options.
- Dental coverage through Delta Dental or a reimbursement account for flexible coverage.
- Vision plan with a national network.
- HSA and FSAs for eligible expenses.
- Competitive retirement package.
- Continuing education and advancement opportunities.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
