US Oncology

Oncology Data Engineer - Precision Medicine - Dallas, Tx

US Oncology$110K — $130K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or master's degree in computer science, engineering, or a related field.
  • 7-10 years professional experience in data engineering focusing on ETL processes.
  • 3+ years of healthcare data engineering experience.
  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Strong scripting skills, particularly in Python, and deep knowledge of SQL.

Responsibilities

  • Design, develop, and maintain ETL pipelines for data ingestion from various sources.
  • Support data science efforts by coding with SQL from data warehouses.
  • Implement new data architecture inspired by existing solutions.
  • Optimize ETL workflows for better performance and accuracy.
  • Integrate AI functionalities using OpenAI tools and LLMs.
  • Collaborate with teams to translate requirements into technical solutions.
  • Maintain monitoring systems to proactively identify data platform issues.

Benefits

  • Remote work opportunity, must reside in Texas.
  • Opportunity to work in a cutting-edge oncology-focused environment.
  • Collaborative, cross-functional team interactions.
  • Focus on innovative technologies and AI advancements in healthcare.
  • Commitment to adherence to compliance and ethical standards in oncology.
Full Job Description
Overview

Texas Oncology is looking for a Remote Oncology Data Engineer to join our Precision Medicine team! Must currently reside in Texas.

Please note: Candidates with direct oncology data engineering experience will receive priority consideration.

What does the Oncology Data Engineer do?

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

The essential duties and responsibilities (included but not limited to):

Data Delivery Support
  • 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.

AI and LLM 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.

Collaboration and Support
  • Collaborate with cross-functional teams to understand requirements and translate them into technical solutions.

Monitoring and Maintenance
  • Implement monitoring and alerting systems to proactively identify and resolve platform issues.
  • Perform regular maintenance, updates, and upgrades to cloud infrastructure and associated services.

Documentation and Best Practices
  • 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

The ideal candidate will have the following background and experience:

Education
  • Bachelor's or master's degree in computer science, engineering, or a related field.

Healthcare & Oncology Domain Knowledge
  • 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)

Experience
  • 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.

Technical Skills
  • Strong scripting and automation skills (e.g., Python).
  • Strong experience with SQL required.
  • Experience with GitHub, Confluence, Jira preferred

Soft Skills
  • Excellent problem-solving abilities and attention to detail.
  • Effective communication and teamwork skills.
  • Ability to manage multiple priorities in a challenging environment.


Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations will be offered to enable individuals with disabilities to perform the essential functions. 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 characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations will be offered to enable individuals with disabilities to perform essential functions. The work environment is typical of an office setting.

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