Job Description
Job DescriptionAbout the Client
Our client is a rapidly growing technology company at the intersection of healthcare and artificial intelligence. Founded by a team of industry veterans and academic leaders, this organization is on a mission to make high-quality clinical data more accessible for innovation in AI-driven healthcare. They are building a next-generation platform to support the development, training, and validation of responsible AI models with a strong emphasis on data quality and patient safety.
About the Role
The company is looking for a skilled Analytics Engineer to help shape, validate, and refine large-scale healthcare datasets for use in clinical research and AI product development. This role plays a crucial part in harmonizing complex, multimodal data from diverse healthcare environments into usable, well-documented formats for data scientists and AI teams.
Responsibilities
-
Design and maintain robust data transformation pipelines using tools such as dbt and Snowflake, prioritizing data integrity and transparency.
-
Normalize and integrate various types of clinical data—including structured records, unstructured notes, imaging, and more—into a unified ontological model.
-
Collaborate with engineering teams to optimize de-identification and ETL workflows from multiple cloud-hosted healthcare data sources.
-
Partner with NLP experts to develop methods for extracting structured clinical information from text-based sources.
-
Apply CI/CD and version control best practices within analytics codebases.
-
Translate complex research and modeling requirements into scalable data engineering solutions in collaboration with technical stakeholders and external partners.
Requirements
Required:
-
At least 3 years of experience in analytics or data engineering.
-
Strong proficiency with SQL and dbt.
-
Bachelor's degree in a technical or quantitative field.
-
Hands-on experience with cloud platforms (especially Snowflake and/or AWS).
-
Competency in Python for data wrangling and feature generation.
-
Familiarity with AI/ML workflows and deployment pipelines.
-
Commitment to clean, modular, and well-documented code using software engineering best practices.
-
Comfort working in a dynamic, fast-paced startup setting.
-
Clear communication skills and the ability to advocate for robust data practices.
-
Passion for advancing healthcare through trustworthy and scalable data infrastructure.
Preferred:
-
Experience with healthcare data standards such as HL7, FHIR, or DICOM.
-
Background in academic medical research.
-
Visualization experience using tools like Tableau, Power BI, Hex, or Python libraries.
-
Exposure to integrating LLM tools and frameworks (e.g., RAG, agent workflows) within analytics pipelines.
Benefits & Why Join
-
Competitive compensation package: base salary in the $145K–$160K range plus equity.
-
Opportunity to work at the forefront of AI and healthcare innovation.
-
Collaborative and mission-driven team environment.
-
Flexibility to work remotely or from the company’s office in New York.
-
A chance to make a real-world impact by shaping the future of clinical AI and healthcare research.