Business Data Analyst (Oncology Data Mapping)

Role: Oncology Data Mapping Specialist (Business Analyst)

Location: Remote

Overview

We are seeking highly skilled contractor(s) to support the mapping and modeling of oncology EMR and genomics data into a common data model, specifically targeting FHIR mCODE. This role is critical to advancing our data integration efforts and enabling scalable, interoperable analytics across oncology datasets.

Key Responsibilities

Map oncology EMR (Onco EMR or similar) and genomics source data to a targeted schema (FHIR mCODE or similar).

Analyze and interpret back-end tables, schemas, and content structures of oncology EMR systems.

Collaborate with clinical and technical teams to understand data abstraction workflows and front-end EMR interfaces.

Write and execute SQL or Python code to transform source tables into the target data model.

Operate within a Databricks Medallion architecture to develop, test, and deploy data pipelines across bronze, silver, and gold layers.

Maintain version control and collaboration using Git.

Document mapping logic, transformation rules, and data lineage.

Collaborate with cross-functional teams in an AGILE framework, adapting to evolving requirements and delivering incremental value through iterative development cycles.

Participate actively in SCRUM ceremonies such as daily stand-ups, sprint planning, sprint reviews, and retrospectives to ensure project transparency and continuous improvement.

Required Qualifications

Proven experience with oncology EMR systems, including back-end schema and table structures.

Strong understanding of genomics data and its integration into clinical models.

Hands-on experience with FHIR mCODE or similar healthcare data models.

Proficiency in SQL and Python for data transformation and modeling.

Experience working in Databricks, with knowledge of Medallion architecture principles.

Familiarity with Git for version control and collaborative development.

Solid understanding of standard clinical terminologies and code sets, including:

ICD-10-CM/PCS

SNOMED CT

LOINC

RxNorm

NDC

Preferred Qualifications

Experience with front-end EMR workflows and clinical data abstraction.

Experience using terminology tooling such as Health Language.

Background in clinical informatics, data engineering, or data science.

Ability to work independently and communicate effectively with cross-functional teams.