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Data Engineer

Join the Team Where Talent and Passion Improve Cancer Care

It is hard to find someone in today’s world who hasn’t been impacted by cancer. At OncoLens, we envision a world where every cancer patient has access to the best possible minds, therapies, and innovations in care—in time to make a difference. We deliver tech-based solutions for cancer care professionals and life science companies to improve treatment plans and save lives.

OncoLens is the leading data and clinical decision support hub that supports the multi-disciplinary discussion of cancer cases by experts and care teams, clinical trials, and research and tracking for the highest potential quality or outcome for the patient. More than 10% of all cancer centers in the United States count on OncoLens to help improve outcomes through coordinated patient data, in-depth analysis, and actionable clinical decision support

OncoLens is a global, venture-backed healthcare company, serving some of the largest integrated delivery networks and national cancer institutes across the country.

Join our team to get hands-on knowledge of not only the technology that powers OncoLens but also exposure to the day-to-day business and strategy decisions in a rapidly growing company.

We’re looking for a Data Engineer who is a self-starter and energized by working on a dynamic team. 

Excited to learn more? Apply using the form provided below.

Data Engineer Position Details

What You’ll Do

  • Develop and maintain our data warehouse in Snowflake, ensuring optimal performance and scalability for healthcare-specific data.
  • Create and optimize ETL/ELT processes using tools like dbt (data build tool) to transform raw healthcare data into actionable insights.
  • Collaborate with data scientists to build and deploy machine learning models, particularly in NLP for medical text analysis.
  • Implement data quality checks and monitoring systems to ensure the integrity and reliability of our healthcare-related data assets.
  • Build internal tools to manage and grow the OncoLens Oncology Knowledge Base, an informatics database that powers insights
  • Design and implement robust data tooling to process and analyze healthcare data from various sources, including FHIR, JSON-based REST APIs, and other healthcare-specific formats.
  • Work closely with cross-functional teams to understand healthcare business requirements and translate them into technical solutions.
  • Contribute to the design and development of data-driven products and features that directly impact patient care, tumor board efficiency, and clinical trial matching.
  • Utilize Sigma for creating interactive, self-service BI dashboards and reports for healthcare data analysis.

What You Should Have

  • Bachelor’s degree in Computer Science, Data Science, Bioinformatics, or a related field. Advanced degree is a plus.
  • 5+ years of professional experience in data engineering, preferably in healthcare-related fields.
  • Strong proficiency in Python, including experience with data processing libraries (e.g., Pandas, NumPy) and ML frameworks (e.g., scikit-learn, PyTorch).
  • Expertise in SQL and experience with cloud-based data warehouses, particularly Snowflake.
  • Hands-on experience with dbt for data transformation and analytics engineering in a healthcare context.
  • Familiarity with cloud platforms, preferably AWS, including services like S3, Redshift, and Lambda.
  • Experience with data modeling, schema design, and optimization for both analytical and operational databases, particularly for healthcare data.
  • Knowledge of healthcare data standards (e.g., FHIR, HL7) and experience working with medical data is highly desirable.
  • Familiarity with clinical trial data structures and experience in developing algorithms for patient-trial matching.
  • Strong problem-solving skills and ability to work independently in a fast-paced healthcare informatics environment.

What You Might Also Have

  • Experience with NLP techniques and libraries, particularly John Snow Labs’ Spark NLP for Healthcare, for medical text analysis.
  • Proficiency in using Sigma for creating and maintaining business intelligence dashboards and reports in a healthcare setting.
  • Familiarity with distributed computing frameworks like Apache Spark for large-scale healthcare data processing.
  • Experience with real-time data streaming technologies (e.g., Kafka, Kinesis) for continuous healthcare data updates.
  • Knowledge of data visualization tools (e.g., Tableau, PowerBI) and experience creating dashboards for healthcare metrics.
  • Understanding of HIPAA compliance and healthcare data privacy regulations.
  • Experience with Agile methodologies and DevOps practices in a healthcare technology setting.
  • Knowledge of clinical trial design, protocols, and data management systems.

What You’ll Learn at OncoLens

  • Be part of a “startup within a startup” -the opportunity to be exposed to high-level leadership and to contribute to the steering and development of a new healthcare SaaS product.
  • Deep insights into the healthcare industry and how technology can directly impact patient outcomes, particularly in cancer care.
  • Building a real-time data framework, where the infrastructure, data, and business logic are all coded, rather than using traditional data tools and configuration.
  • Hands-on experience with cutting-edge technologies in data engineering and machine learning applied to real-world medical challenges.
  • The intricacies of working with sensitive patient data and maintaining strict compliance standards.
  • Exposure to the full lifecycle of a rapidly growing healthcare technology startup, including clinical trial matching technologies.
  • Collaboration with multidisciplinary teams, including oncologists, data scientists, and product managers focused on improving patient care and clinical trial enrollment.

Excited to learn more? Apply using the form provided below.

Apply Now

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