Remote Oncology Data Engineer - Precision Medicine - Dallas, Tx

Overview

Texas Oncology is looking for a Remote Oncology Data Engineer to join our Precision Medicine team! This position is based out of the corporate office in Dallas, Texas.
Texas Oncology is the largest community oncology provider in the country and has approximately 600+ providers in 300+ sites across Texas and southeastern Oklahoma. Our founders pioneered community-based cancer care because they believed in making the best available cancer care accessible to all communities, allowing people to fight cancer at home with the critical support of family and friends nearby. Our mission is still the same today – at Texas Oncology, we use leading-edge technology and research to deliver high-quality, high-touch, evidence-based cancer care to help our patients achieve "More breakthroughs.

More victories." in their fight against cancer. Today,
Texas Oncology treats half of all Texans diagnosed with cancer on an annual basis.

Come join our team that is responsible for helping lead Texas Oncology in treating more patients diagnosed with cancer than any other provider in Texas. We offer our employees a competitive benefits package that includes Medical, Dental, Vision, Life Insurance, Short-term and Long-term disability coverage, a generous PTO program, a 401k plan that comes with a company match, a Wellness program that rewards you practicing a healthy lifestyle, and lots of other great perks such as Tuition Reimbursement, an Employee Assistance program and discounts on some of your favorite retailers.

At Texas Oncology, we recognize the long-term impact of our people and are committed to rewarding performance and potential. That's why select roles may be eligible to participate in our Long-Term Incentive Plan (LTIP): an incentive program designed to attract, retain, and reward top talent.

Long-Term Incentive Plan (LTIP): is an incentive program that typically vests over a three-year period and is tied to both individual performance and the operational success of Texas Oncology. Awards are discretionary and based on your position, performance, and potential for future career growth at Texas Oncology. Awards are reviewed and approved during the annual compensation review. LTIP awards are subject to your continued employment through the award payment date, and are governed by the written terms and conditions of the LTIP document.

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.

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

• 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.

The ideal candidate will have the following background and experience:

• 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.,…