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Remote Oncology Data Analyst Jobs (NOW HIRING)

Analytics:deliver analytic applications & services that generate insight on how to measurably ... Remote Travel: N/A Who you are This position will be responsible for abstraction and data entry of ...

Analytics: deliver analytic applications & services that generate insight on how to measurably ... Remote Travel: N/A Who you are This position will be responsible for abstraction and data entry of ...

Remote Department: Clinical Quality Registry Services Schedule: Part time, 20 hours Salary: $28.35 ... complex analysis utilizing specialty databases to extract patient data from electronic medical ...

... LI-Remote #ADSI #internalops What You Will Do Perform complex analysis utilizing specialty ... Oncology Data Specialist credentialed from the National Cancer Registrars Association (NCRA ...

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Remote Oncology Data Analyst information

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$34K

$82.6K

$136K

How much do remote oncology data analyst jobs pay per year?

As of Jun 14, 2026, the average yearly pay for remote oncology data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Oncology Data Analyst, and why are they important?

To thrive as a Remote Oncology Data Analyst, you need strong analytical skills, a background in health data or biostatistics, and familiarity with oncology terminology, often supported by a degree in health informatics, statistics, or a related field. Proficiency with data analysis tools such as SQL, SAS, or R, and experience with electronic health records (EHRs) or cancer registry software like SEER*DMS are typically required. Attention to detail, problem-solving abilities, and effective remote communication skills help you stand out in this position. These skills ensure accurate data interpretation, support oncology research and patient outcomes, and enable efficient collaboration in a remote work environment.

What are some common challenges faced by Remote Oncology Data Analysts, and how can they be addressed?

Remote Oncology Data Analysts often face challenges such as ensuring data accuracy across various electronic health record systems and maintaining effective communication with clinical teams. Working remotely also requires strong self-motivation and organization to manage multiple projects and data requests simultaneously. To address these challenges, it's important to establish clear documentation practices, use secure data-sharing platforms, and participate in regular virtual meetings to stay aligned with team goals. Building strong relationships with clinical staff and IT support can also help overcome technical and data integrity issues.

What is a Remote Oncology Data Analyst?

A Remote Oncology Data Analyst is a professional who analyzes cancer-related data while working from a remote location, such as their home. They collect, organize, and interpret clinical and research data to support oncology programs, improve patient outcomes, and inform decision-making. Their work often involves using specialized software to manage large datasets, ensuring data accuracy and compliance with regulations. They collaborate with healthcare providers, researchers, and administrators, playing a crucial role in advancing cancer treatment and research.
More about Remote Oncology Data Analyst jobs
What cities are hiring for Remote Oncology Data Analyst jobs? Cities with the most Remote Oncology Data Analyst job openings:
What are the most commonly searched types of Oncology Data Analyst jobs? The most popular types of Oncology Data Analyst jobs are:
What states have the most Remote Oncology Data Analyst jobs? States with the most job openings for Remote Oncology Data Analyst jobs include:
Infographic showing various Remote Oncology Data Analyst job openings in the United States as of June 2026, with employment types broken down into 62% Full Time, 15% Part Time, and 23% Contract. Highlights an 100% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Remote Oncology Data Engineer - Precision Medicine - Dallas, Tx

Remote Oncology Data Engineer - Precision Medicine - Dallas, Tx

The US Oncology Network

Dallas, TX • Remote

$104K - $126K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


US Oncology rating

7.4

Company rating: 7.4 out of 10

Based on 104 frontline employees who took The Breakroom Quiz

251st of 872 rated healthcare providers


Job description

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. 

Why work for us? 

Come join our team that is responsible for helping lead Texas Oncology in treating more patient 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.  

Join a Team That Invests in Your Future

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.

What is the Long-Term Incentive Plan (LTIP)?

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.

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.

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.

Education:UNAVAILABLEEmployment Type: FULL_TIME

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