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, supporting discovery, access, combination, and analysis 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 focuses on designing, building, and supporting scalable data products, pipelines, integrations, and services for complex biomedical research use cases. The engineer will work with large-scale genomic and multimodal datasets and translate 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 data structures and standards, metadata and provenance maintenance, data quality validation, and enabling secure, governed access to research datasets. The role requires substantial research informatics experience, including genomic or other omics data, 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. The engineer will work independently with bioinformaticians, computational scientists, investigators, laboratory personnel, and other research stakeholders. The position uses Google Cloud Platform and cloud-native technologies such as BigQuery, Cloud Storage, Dataflow, Batch, and Pub/Sub. Experience with modern AI-assisted and agentic development tools, such as Claude Code or OpenAI Codex, is required for software development, data engineering, testing, troubleshooting, documentation, and code quality. The engineer develops and deploys data pipelines, integrations, and transformations for analytics and machine learning applications and solutions 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 turn 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 work based on business needs.
Requirements
- Bachelor’s degree in a relevant analytical or quantitative field and at least five years of professional or research experience in data visualization, data engineering, or analytical modeling techniques; or an associate’s degree in a relevant field and at least seven years of such experience. In-depth business or practice knowledge may also be considered.
- Substantial research informatics experience, including experience with genomic and/or other omics data.
- Knowledge of 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.
- 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 (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.
- Ability to manage varied project workloads and multiple priorities; interpersonal, time management, cross-functional teamwork, analytical, customer service, verbal and written communication, attention-to-detail, learning, and problem-resolution skills.
- Ability to work independently with research stakeholders.
- Experience using modern AI-assisted and agentic development tools such as Claude Code, OpenAI Codex, or comparable platforms.
- Must be located within 100 miles of a Mayo Clinic campus for occasional on-site expectations.
- This vacancy is not eligible for sponsorship, and Mayo Clinic will not sponsor or transfer visas for the position. 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, 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 (GCP) certification.
Responsibilities
- Design, build, and support scalable data products, pipelines, integrations, and services for complex biomedical research use cases.
- Ingest and transform research data, integrate information across clinical and research systems, and 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 for genomic and multimodal datasets.
- Develop and deploy data pipelines, integrations, and transformations supporting analytics and machine learning applications and solutions.
- Partner with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data, conduct exploratory analysis, transform data, build and validate analytical models, and translate assessments into actionable insights.
- Work with bioinformaticians, computational scientists, investigators, laboratory personnel, and other research stakeholders.
- 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
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
