Clinical Data Engineer

Summary

Join N-Power Medicine as a Clinical Data Engineer and contribute to the development of a cutting-edge data platform for accelerating cancer care. You will collaborate with cross-functional teams to design and implement data pipelines, support prospective trial matching, and prepare data for AI/ML model training. This remote position within the United States requires a bachelor's degree and 5+ years of relevant experience in healthcare data engineering. You will leverage your expertise in clinical interoperability standards, programming languages (Python, SQL), and data engineering in cloud platforms. The role involves robust document management and collaboration with data science, biostatistics, and engineering teams. N-Power Medicine offers a competitive salary, equity, a discretionary annual bonus, and company benefits.

Requirements

• A bachelors’ degree with 5+ years of experience in healthcare data engineering, reference/master data management, document management, and source data verification
• Demonstrable technical expertise and domain knowledge gained through a combination of formal education and practical experience
• Knowledge of clinical interoperability and terminological data standards, including FHIR, HL7, C-CDA, and OHDSI/OMOP
• Substantial experience with object oriented and functional programming in Python
• Experience with data engineering in at least one major cloud platform
• Proficiency in SQL and other methods of data wrangling
• Experience with electronic document ingestion, classification, indexing, storage and retrieval in a data lake environment
• Ability to communicate technical information to technical and non-technical audiences alike
• Able to thrive in ambiguity, adapting effectively to evolving priorities and uncertainties
• Generous, Curious & Humble

Responsibilities

• Contribute to the design and implementation of NPM’s data platform, with a focus on robust document ingestion, classification, and storage strategies, including writing foundational code and implementing workflows in Databricks
• Partner with data science, biostatistics, and engineering groups to develop pipelines and data features that support prospective trial matching
• Maintain ETL processes that marry and enrich practice data, including handling large-scale document ingestion and metadata enrichment
• Collaborate with product and program teams to support secondary offerings to the life science sector
• Prepare the data required to train and validate diverse AI and ML models
• Collaborate with the Data Science team to develop and implement innovative solutions for electronic document management, including classification, storage, retrieval, and archiving to support AI-driven processes and enable efficient source data verification

Preferred Qualifications

• Experience in electronic document storage, retrieval and archiving processes and metadata management within a data lake or pharma industry solutions like Veeva Vault
• Experience developing project plans and exposure to standard project/product/program management paradigms
• AWS experience and Databricks experience
• Experience with oncology data and the application of specialized standards, like mCODE, SEER, NAACR, PRISSMM, to the representation and analysis of that data
• Domain competencies with electronic health record (EHR) (e.g. OncoEMR), practice management (e.g. Centricity), next-generation sequencing (NGS), clinical trial management (CTM), pharmacy specific to antineoplastic medications, laboratory and other healthcare ancillary systems

Benefits

• Remote work within the United States
• Expected salary range for this position is $150,000 and $185,000
• Equity at hire
• Discretionary annual bonus which may be available based on Company performance
• Company benefits
• 401K plan
• Other great company “perks.”