CEDENT- Clinical Data Engineer ()

Job Duties/Essential Functions

Design, build, and test Databricks workflows and jobs for both batch and streaming
Design clinical architecture and develop, implement frameworks such as Common Data Models (OMOP, CDISC, FHIR7, etc.) and techniques to organize clinical data from disparate sources.
Design a secure, cloud-based platform for acquiring and aggregating patient data to then be consumed by analytics workflows.
Collaborate with clinical data experts to select and implement ontologies (ICD10, SNOMED, RxNorm, etc) and to translate between disparate ontologies.
Implements repeatable techniques and methods around data transfer, pipeline testing, and platform infrastructure and management components.
Creates extract tools utilizing CDC, API’s, and SDK’s from source systems like Medrio and other EDC’s to hydrate the Lakehouse.
Creates SQL and Pyspark notebooks and packages to facilitate the movement, cleaning, and storage or data.
Enhancing functionality and scalability of the client services through technology innovations
Adhering to and promoting high standards in testing and integration. This includes writing unit tests as well as integration or pipeline tests.
Collaborating with other teams, including biological imaging, cancer biology, clinical data, and engineering

Competencies

Attention to detail
Ability to work both independently and as part of a team
Ability to design and develop robust, scalable cloud-based solutions

Required Education and Experience

Degree in Computer Science or related field desired
5-7 years relevant experience
Must have experience in one or more pipeline or orchestration tools (Databricks, Snowpipes, Apache Airflow, SQL server integration services, AWS step functions, Synapse, etc.) Databricks is preferred.
Must have experience working with SQL (any) and be able to craft advanced level queries.
Understands REST API’s and how to utilize them to acquire and send data.
Appropriate understanding of Git and source control.
Must have experience working with and implementing data lakes.
Must have advanced ability in at least one major language including: python, Pyspark, SQL, Scala.
Must have experience with clinical data, maintaining clinical data lifecycle and implementing common data models. Preference is given to someone who has combined data into a single ontology from multiple disparate data sources.
Prior experience working with OMOP, CDM, and FHIR preferred
Prior experience working in biotech, clinical, healthcare, or life sciences preferred
Experience with modern mathematical and statistical software, and preferably AI/ML frameworks desired

Certifications/Specializations

No certifications or specializations required.
Databricks or other Lakehouse platform (Fabric, Snowflake, GCP, AWS, etc.) certifications are preferred.

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