The US Oncology NetworkRemote
Remote Oncology Data Engineer - Precision Medicine - Dallas, Tx
United States of America
Full Time
1 hour ago
H1B Sponsor Likely
Key skills
ETL processesData engineeringSQLPythonCloud platformsAWSAzureGCPOpenAI toolsLarge language modelsHealthcare data standardsHL7FHIRICD-10LOINCSNOMEDEHR dataOncology workflowsMolecular/genomic dataLaboratory data integrationPathology data integrationMolecular testing data integrationGitHubConfluenceJiraPriority managementAILLMOpenAIETLData EngineeringCommunication
About this role
The US Oncology Network is the largest community oncology provider in the country, dedicated to providing high-quality cancer care. They are seeking a Remote Oncology Data Engineer to support the Precision Medicine team by designing and building data pipelines, integrating AI technologies, and collaborating with cross-functional teams to enhance data delivery and informatics decision-making.
Responsibilities:
- Design, develop, and maintain robust ETL pipelines for large-scale data ingestion and transformation from various sources such as Electronic Medical Records (EMRs), lab interfaces, and data warehouses
- Support data science initiatives with SQL coding from various data warehouses
- Implement new data architecture, drawing inspiration from existing pipelines
- Optimize ETL workflows for performance and accuracy, ensuring seamless data integration
- Integrate AI functionalities into data platforms using OpenAI tools and LLMs
- Collaborate with AI teams to implement AI-driven solutions within the data pipeline
- Stay updated on the latest advancements in AI and LLM technologies to enhance platform capabilities
- Collaborate with cross-functional teams to understand requirements and translate them into technical solutions
- Implement monitoring and alerting systems to proactively identify and resolve platform issues
- Perform regular maintenance, updates, and upgrades to cloud infrastructure and associated services
- Maintain comprehensive documentation of system architectures, processes, and procedures
- Advocate for and implement best practices in cloud engineering, SQL coding, ETL processes, and AI integration
Requirements:
- Bachelor's or master's degree in computer science, engineering, or a related field
- Understanding of oncology workflows and clinical data types
- Familiarity with molecular/genomic data (e.g., NGS, variants, biomarkers)
- Experience integrating laboratory, pathology, and molecular testing data
- Knowledge of healthcare data standards (HL7, FHIR, ICD-10, LOINC, SNOMED)
- Experience working with EHR data (e.g., IKMg1/IKMg2, Epic, Copia)
- 7–10 years of professional experience in data engineering with a focus on ETL processes
- Strong background in cloud platforms (e.g., AWS, Azure, GCP)
- Experience with OpenAI tools and integrating AI functionalities, including LLMs, into data platforms
- Strong scripting and automation skills (e.g., Python)
- Strong experience with SQL required
- Excellent problem-solving abilities and attention to detail
- Effective communication and teamwork skills
- Ability to manage multiple priorities in a challenging environment
- Experience with GitHub, Confluence, Jira preferred