Clinical Data Engineer II/III

Job Description

Job Description

ClearNote Health is an early cancer detection company focused on the development and commercialization of non-invasive epigenomic tests to detect cancer through a standard blood draw, earlier than existing methods and when the disease is still treatable. Leveraging its novel liquid biopsy technology, ClearNote Health is initially focused on high-mortality cancers with the greatest need for early detection, starting with pancreatic and ovarian cancers.

Position Summary :
The Clinical Data Engineer II/III owns clinical Data Operations: the data pipelines, data warehouse, and reporting infrastructure that transform clinical data, laboratory data, and sequencing results into validated, audit-ready clinical and business data. This position operates in a regulated environment in which accuracy and traceability are as important as well-architected code. The role combines hands-on pipeline and data-modeling work with ongoing production data support for our clinical study operations and is central to the integrity of the data that informs our research and clinical decisions.

Key Responsibilities:

• Build and maintain ELT pipelines from clinical source systems — and non-standard sources such as  ad hoc spreadsheets — into our data warehouse, and design ingestion frameworks that adapt to evolving report formats 
• Support bulk data transfer initiatives to external partners and client-facing destinations, including the definition of the data contracts those partners depend on 
• Develop, test, and refactor data transformation models across core clinical schemas, implementing precise, well-specified business logic, and integrate clinical data with other corporate data 
• Define methods and metrics for assessing data quality, and monitor and maintain data quality across clinical datasets 
• Own the reliability of clinical result data end to end, tracing issues to their root cause and strengthening controls through documented change management 
• Strengthen the resilience of data contracts and design reconciliation logic that unifies data from multiple sources into a single, authoritative record 
• Serve as a trusted partner to clinical and laboratory operations and external stakeholders, resolving data questions and improving accuracy at the source 
• Build and maintain dashboards and monitoring, including those subject to formal system validation, and support the data needs of adjacent business systems 
• Partner with the Regulatory/QA team to ensure clinical data flow and the data warehouse remain compliant with procedural and regulatory requirements 
• Serve as a subject-matter expert on warehouse clinical data, providing technical guidance and training to research and development teams 
• Provide project status updates to cross-functional stakeholders 

Qualifications :

• Bachelor’s degree required, Master’s degree preferred, in Computer Science, Information Systems, Data Engineering, or a related field.
• 5+ years of hands-on data engineering experience with production data-transformation frameworks (dbt preferred) and a cloud data warehouse 
• Software-engineering fundamentals and an expert understanding of database and data-warehouse concepts 
• Deep SQL expertise, including the ability to identify subtle logic errors in complex queries 
• Experience with ELT and data-integration tools 
• Experience with designing, building and using containers 
• Proficiency in Python or a comparable scripting language 
• Familiarity with cloud identity and access-management concepts (key-pair authentication, OAuth/OIDC, workload identity federation) 
• Proven ability to work in a regulated environment, including precise documentation, change-control processes, and audit trails 
• Enjoys a role that balances building new data systems with keeping production systems reliable and trusted 
• Strong written and verbal communication skills, with a track record of documenting your work 
• Working knowledge of clinical or laboratory data systems is a plus 
• Familiarity with clinical data standards (CDASH/CDISC) preferred 
• Working knowledge of Good Clinical Practice (GCP) and the clinical trial process preferred 
• Familiarity with cancer-related medical classifications and ontologies (e.g., ICD-10) a plus 

On-site is preferred for this position, in either our San Diego or San Mateo office. The anticipated salary range for this position is $150,000 - $190,000. The actual salary will be dependent on various factors that may include experience level, knowledge, skills, and abilities.

ClearNote Health offers a competitive salary and benefits package.

Come join us in addressing large healthcare needs through precision epigenomic medicine!

ClearNote Health is an exciting life science company that is reinventing non-invasive molecular diagnostic testing using next generation epigenomic technologies. We are passionate and dedicated to discovering and developing medicines that will make a significant difference in cancer and other epigenomic-driven diseases. Our technologies provide novel insight and quantitation of human health and disease, with our focus on precision medicine applications improving both clinical and health system outcomes. Our company was founded based on pioneering work in the Stanford laboratory of Stephen Quake, with advisors from Stanford and UCSF.

We look for extraordinary lifelong learners with a passion and growth mindset for these areas, and for combining biological ingenuity with AI and data analysis. Led by a team with decades of experience bringing products from concept to market, we are an equal opportunity employer and value diversity at our company.

We provide generous benefits to all employees including stock options. We are building a world-class company, based in San Diego and San Mateo.

Our commitment to Diversity, Equity, Inclusion, and Belonging:

We celebrate diversity in perspectives and backgrounds, and this is reflected in our innovation, our mission, and values. Our differences make us unique, help us innovate, and allow us to persevere. We strive to achieve representation and inclusion and redefine the possible in patients living longer lives.

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