Note: The job is a remote job and is open to candidates in USA. Beacon is a high-growth healthcare AI company seeking an Analytics Engineer to join their data team. The role involves owning the transformation layer of a modern ELT pipeline, ensuring data quality and optimizing pipeline performance to support clinical AI development.
Responsibilities
- Query complex source systems across EMR, ECG, and DICOM data to identify and map data elements supporting AI training and patient journey analyses
- Develop and maintain data transformation pipelines using dbt and Snowflake, ensuring data quality, lineage, and transparency
- Harmonize multimodal data from multiple health systems into a unified ontological layer, with input from clinical experts
- Perform complex data extraction, manipulation, and summarization to create analytical data models
- Implement data quality tests, CI/CD, and version control best practices across the data modeling pipeline
- Support software engineers in optimizing de-identification and ETL processes across disparate health system cloud environments
- Work with NLP experts to structure and model discrete clinical concepts abstracted from unstructured text
- Collaborate with technical and clinical SMEs and customers to translate research and model requirements into engineering solutions
Skills
- Bachelor's degree in a quantitative field (Data Science, Biomedical Informatics, Computer Science, Biostatistics)
- 3+ years in analytics or data engineering roles with hands-on cleaning and structuring of clinical/EHR data
- Strong dbt and SQL proficiency: reusable Jinja macros, custom tests, multi-environment deployments
- 1+ years extracting, curating, and analyzing HIT/healthcare delivery data (EMR, claims, registry); familiarity with FHIR, CDA, CQL, and clinical terminology standards (ICD, CPT, LOINC, SNOMED-CT, NDC, RxNorm) a plus
- Comfort in a cloud environment (Snowflake and/or AWS preferred)
- Proficiency with Git and version control workflows
- Advocate for software engineering best practices (modularity, unit testing, clean documentation) within a data science team
- Comfortable with ambiguity in a fast-paced, early-stage startup environment
- Excellent communication skills, able to translate customer needs into data solutions
- LLM/RAG integration experience (Snowflake Cortex, Bedrock, Azure OpenAI)
- Python for data cleaning/feature engineering
- Exposure to AI/ML modeling teams
- Epic/Cerner/Allscripts familiarity
- Medical ontology or DICOM/imaging experience
- OMOP common data model
- Agile tooling (Jira/Linear)
- Dbt Cloud
Benefits
- Remote work and flexible hours, with meetings kept to a healthy minimum
- Comprehensive wellness benefits: healthcare, dental, vision, PTO, sick days
- Professional development days
- Collegial, academically-minded culture with startup speed and flexibility
- Strong balance of focus time and easy access to collaborators
- Mission-driven company focused on improving patient care through AI
Company Overview
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