Research Data Engineer

Overview:

Vibrent is a high-performance organization committed to driving innovation and delivering exceptional value to clinical research, biotech, and academic medical centers. We thrive on a culture of resilience, continuous improvement, and collaboration. Our mission is to grow the business while delighting our customers, and we embrace a 'one team' mindset to achieve shared success.

As a Research Data Engineer at Vibrent Health, you will bridge the gap between research methodology and engineering implementation. You will ensure that the data collected via apps, wearable devices, EHR integrations, and other digital health sources are transformed into research-ready datasets. Your work will empower researchers and data scientists to derive meaningful insights that improve health outcomes at scale.

Vibrent is a remote first organization. You will be equipped to work from your home office or other working location.

Responsibilities for this role will include, but not be limited to:

• Design, maintain, and optimize data models to create robust, research-ready datasets.
• Harmonize and standardize variables, ensuring consistent naming conventions, clear definitions, and logical coding schemas.

• Build and refine ETL processes using SQL and Python to transform raw health data into structured formats suitable for analysis.
• Collaborate with engineering teams to ensure data pipelines are reliable, scalable, and performant.

• Partner with Vibrent’s research teams to understand study protocols and data requirements.
• Translate research questions into optimized queries, aggregations, and summaries that facilitate quick, accurate analysis.

• Develop custom dashboards, reports, and interactive visualizations (e.g., Tableau, Looker, or Python-based libraries) to empower stakeholders with real-time access to quality metrics and research findings.

• Create and maintain comprehensive data dictionaries, metadata standards, and codebooks to enhance data transparency and reproducibility.
• Conduct periodic data quality checks and audits to ensure compliance with research standards and regulatory requirements.

• Work closely with engineers, product managers, and researchers to integrate research needs into the product roadmap.
• Participate in code reviews, agile sprints, and continuous improvement initiatives.

• Master’s or Ph.D. in a relevant field (e.g., Epidemiology, Public Health, Health Informatics, Biostatistics, Data Science) or equivalent professional experience.
• Proven track record of handling health/clinical datasets and supporting research analysis.
• Proficiency in SQL and Python, with experience creating ETL pipelines and implementing data modeling best practices.
• Familiarity with cloud-based data warehousing (e.g., AWS Redshift, Snowflake, BigQuery) and version control (Git).
• Experience with BI tools and data visualization methods.

• Excellent communication and teamwork skills, with the ability to collaborate effectively in an interdisciplinary environment.
• Passion for advancing digital health research and improving population health outcomes.

When you work at Vibrent, you are surrounded by a diverse group of people who share a passion for achieving excellence and making a lasting impact. Passion, excellence and impact should be rewarded, and we do that-- offering a competitive compensation package that includes over-average 401k match, the benefits you need to prioritize self and family care, and support for your further education and career development. One of the greatest benefits Vibrent offers is opportunity. At Vibrent, we work with the latest tools and technologies including enterprise mobile apps, fitness sensors, medical devices, cloud computing, machine learning, big data and analytics. We partner with national leaders in healthcare, technology, and research. We create tools that will change and improve healthcare for ourselves and future generations.

Vibrent is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.

#LI-LJ1