Oncology Data Engineer

Role Description

The Oncology Data Engineer will support Precision Medicine's data delivery team, design and build robust data pipelines and implement new data architecture to support informatics decision-making. Leveraging deep understanding of ETL methodologies, and AI technologies, the Oncology Data Engineer will create scalable and efficient solutions using innovative technology, including SQL, OpenAI tools and large language models (LLMs).

Supports and adheres to US Oncology Compliance Program, to include the Code of Ethics Business Standards.

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.

Qualifications

• 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.
• Experience with GitHub, Confluence, Jira preferred.
• Excellent problem-solving abilities and attention to detail.
• Effective communication and teamwork skills.
• Ability to manage multiple priorities in a challenging environment.

Physical Demands

• 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.

Work Environment

• The work environment is typical of an office setting.