Senior Data Engineer - Hybrid

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.

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.
This vacancy is not eligible for sponsorship/we will not sponsor or transfer visas for this position.  Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program.