Senior Data Engineer - Hybrid

Mayo Clinic; Rochester (MN); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Mayo Clinic seeks a Senior Data Engineer for the Research Data Atlas, focusing on building an enterprise research data platform across genomic, clinical, and imaging data domains. You will design scalable data products and pipelines, partner with scientists, and enable secure, governed access to complex datasets.

You will work with Google Cloud Platform tools (BigQuery, Dataflow, Pub/Sub) and emerging AI-assisted development tools to translate research requirements into robust data solutions.

Qualifications

• Experience with genomic/omics data and data governance.
• Strong background in research informatics and data quality.
• Ability to translate scientific needs into scalable data solutions.

Responsibilities

• Design, build, and support scalable data products and pipelines for biomedical research.
• Ingest, transform, harmonize, and integrate datasets across studies.
• Ensure data provenance, metadata management, and secure access for researchers.

Skills

Genomics data

Data pipelines

Data modeling

Cloud data platforms

Tools

BigQuery

Dataflow

Pub/Sub

Cloud Storage

Job description

This is a Senior Data Engineering role that will join the Research Data Atlas team, focused on building and advancing Mayo Clinic’s enterprise research data platform. Atlas centralizes, catalogs, integrates, harmonizes, and delivers complex research data so investigators can more easily discover, access, combine, and analyze information across studies and data domains. The platform supports genomic and other omics data, biospecimens, clinical and phenotypic information, laboratory data, imaging, and other research data to enable translational research, precision medicine, artificial intelligence, and advanced analytics.

In this role, your primary focus will be designing, building, and supporting scalable data products, pipelines, integrations, and services for complex biomedical research use cases. You will work with large-scale genomic and multimodal datasets and translate investigator and scientific requirements into technically sound and scientifically appropriate solutions. This includes ingesting and transforming research data, integrating information across clinical and research systems, harmonizing disparate data structures and standards, maintaining metadata and provenance, validating data quality, and enabling secure, governed access to research datasets. A strong background in research informatics is required, including substantial experience with genomic and/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. You must be able to work independently with bioinformaticians, computational scientists, investigators, laboratory personnel, and other research stakeholders.

You will work hands-on with Google Cloud Platform and 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 is required to support software development, data engineering, testing, troubleshooting, documentation, and code quality.

Develops and deploys data pipelines, integrations and transformations to support analytics and machine learning applications and solutions as part of an assigned product team. Demonstrated experience in designing, building, and installing data systems 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, build and validate analytical models, and translate qualitative and quantitative assessments into actionable insights.
This is a hybrid position and must be located within 100 miles of a Mayo Clinic campus for occasional on-site expectations based on business needs.