Data Integration Analyst - Pulmonary Research
Role details
Job location
Tech stack
Job description
This position will be the first technical hire supporting a pediatric pulmonary translational research program. The program's goal is to understand why children differ in respiratory health trajectories and in their vulnerability to environmental exposures, with the long-term aim of developing data-driven approaches that support earlier risk identification and more proactive management.
The role will focus on building reproducible analytic data resources and pipelines that integrate electronic health record, genomic/transcriptomic, environmental exposure, lung function, and other research data to support studies in pediatric asthma, air pollution, lung function trajectories, prematurity-associated lung disease/BPD, and related pulmonary outcomes. The ideal candidate will be comfortable working in an academic medical center environment with clinicians, researchers, and informatics collaborators.
Key priorities include reusable cohort construction, ETL workflows, data modeling, quality control, data provenance, documentation, and privacy-conscious handling of clinical and genomic research data. This is not intended to be a one-off reporting role, but rather a position focused on building durable, reproducible data infrastructure for clinical and translational research.
What you will do
- Collaborate with biomedical researchers to identify and analyze scientific problems that require integration of disparate, highly dimensional data types such as clinical and genomic data.
- Quickly acquire biomedical domain knowledge in order to understand requirements for data integration, optimizing data resources and applications to meet scientific needs.
- Create requirements for complex data integration and application development projects, and translate requirements into deliverables.
- Develop and implement innovative data models that represent complex biomedical data types in usable and accessible schema.
- Write extract, transform, and load (ETL) procedures that combine and recombine biomedical data into new, more useful formats.
- Build and optimize scientific data management, data discovery, reporting, and analysis applications using a combination of off-the-shelf and custom tools.
- Manage small projects and subprojects within larger initiatives, identifying, tracking, and reporting on tasks and deliverables against project timelines.
Requirements
- Bachelor's Degree Required
- Bachelor's Degree in computer/information science, informatics, biomedical engineering, biological science or a related field Preferred
Experience Qualifications
- At least one (1) year of database development/administration, data management, or related experience Preferred
- At least three (3) years of database development/administration, data management, or related experience within a biomedical science or healthcare environment Preferred
Skills and Abilities
- Basic proficiency in data integration, and data architecture
- Basic proficiency in data modeling, ETL, and applications of highly dimensional data types, such as derived from genomics and observational clinical or human subjects research data
- Basic proficiency in source code management, continuous integration, containerization, and automated testing tools and processes
- Fundamental knowledge of programing languages (SQL, Python/Django, JavaScript/HTML, Java, Scala)
- Fundamental knowledge of relational database management systems (PostgreSQL, MySQL, Oracle)
- Fundamental knowledge of biomedical or healthcare data models and standards (HL7, ICD, CPT, SNOMED)
- Strong verbal and written communications skills
- Solid time management skills
- Solid organizational skills
- Solid presentation skills
- Solid project management skills