Data Engineer - Oncology

Texas Oncology is a community oncology provider delivering evidence-based cancer care through technology and research. The Oncology Data Engineer will support the Precision Medicine data delivery team by designing and maintaining scalable ETL pipelines, implementing data architecture, and integrating AI and large language models into data platforms.

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:

• Must currently reside in Texas
• 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
• Minimum 3+ years of professional experience in data engineering in Healthcare
• 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
• Requires sitting for long periods of time
• Some bending and stretching are required
• Adequate finger dexterity and feeling to perform keyboarding and substantial repetitive motions involving the wrists, hands and/or fingers
• Requires vision and hearing corrected to normal range
• Must be able to view computer screens and printed material accurately
• Occasionally lifts and carries items weighing up to 40 lbs
• Candidates with direct oncology data engineering experience will receive priority consideration
• Experience with GitHub, Confluence, Jira preferred