At CancerIQ, our technology is expanding access to precision cancer prevention, early detection, and treatment to more patient populations. We build software and design services that make it easy for health systems to use genetic information to get ahead of cancer at scale. Our best-in-class, science-based platform is proven to double genetic counseling service capacity, quadruple genetic testing uptake, and significantly improve screening compliance.
To date, CancerIQ has raised over $26 million to deliver on our mission, with our Series B funding round led by Merck Global Health Innovation Fund and Amgen Ventures.
Our team is made up of a committed, all-in group of people who are as driven to ending cancer as we know it as the providers and patients we serve. This has led to a growing network of over 200 clinical locations across the country, with a robust ecosystem of partners in the diagnostic and genomics space behind us. But we’re committed to scaling quickly – in this era of tremendous progress against cancer, we’re looking for people to be just as tremendously committed to their work at CancerIQ. If you want your work to matter, join us.
We are seeking a Mid-Level Data Engineer to join our growing team at CancerIQ. The ideal candidate will have a strong foundation in software engineering and data management, with the ability to both maintain and enhance existing codebases and support reporting needs across the organization. This role will involve maintaining pipelines, debugging and updating scripts, optimizing data infrastructure, and ensuring accurate reporting for internal and external stakeholders.
The ideal candidate is excited by the opportunity to work in a mission-driven environment where their skills will directly contribute to improving patient outcomes.
Maintain, debug, and enhance existing ETL processes, data models, and reporting codebases.
Build and optimize data pipelines, integrations, and reports to support operational, clinical, and business analytics.
Collaborate with product, engineering, and customer success teams to understand evolving data needs and translate them into actionable solutions.
Ensure data integrity and reliability across multiple environments (development, staging, production).
Write efficient SQL queries and manage relational databases (primarily PostgreSQL).
Develop and maintain documentation for codebases, data dictionaries, and workflows.
Support ad hoc reporting requests by querying databases and preparing data extracts.
Monitor data jobs and troubleshoot errors proactively.
Implement best practices for data governance, privacy, and security (particularly PHI and HIPAA compliance).
Partner with stakeholders to automate routine reporting tasks and improve accessibility of data insights.
Experience with modern data stack tools (e.g., dbt, Airflow, Fivetran, Snowflake).
Familiarity with healthcare data standards (e.g., HL7, FHIR) or experience working with clinical data.
Knowledge of cloud platforms such as Google Cloud Platform (GCP) or AWS.
Exposure to PHI data handling and HIPAA compliance.
Comfortability with AI tools like ChatGPT for task automation and support.
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