Analytics Engineer - Clinical Data

Job Description

Job Description

About 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.