Senior Data Engineer

About Fullscript

We’re an industry-leading health technology company on a mission to help people get better. We started in 2011 with one simple idea. Make it easier for practitioners to access the products they trust so they can deliver better care. That simple idea grew into a platform that powers every part of care. Today, more than 125,000 practitioners use Fullscript for clinical insights, lab interpretations, patient analytics, education, and access to high-quality supplements.

Over 10 million patients rely on Fullscript to stay connected to their care plans and follow through on treatment. We build tools that make care smarter and more human. Tools that save time, simplify decisions, and help practitioners stay closely connected to the people they care for. When everything they need is in one place, they can focus on what matters most: helping people get better.

This is your invitation. Bring your ideas, your grit, and your care for people. Join us and shape the future of care.

The Opportunity

Fullscript powers care for 125,000+ healthcare practitioners and 10M+ patients by making clinical insights, treatment workflows, and longitudinal data accessible and actionable across the platform. As the Senior Data Engineer, you’ll be part of a small team that turns messy practitioner and clinical data into reliable, analysis-ready assets that enable causal outcome modeling, lab normalization, and strategic patient and prescribing insights.

This role requires healthcare-specific data experience and a practical comfort with semi-structured sources that are common in clinical environments, not just general-purpose data engineering.

What you'll do

Ingest and normalize heterogeneous healthcare data sources including clinical records, lab results, intake forms, and semi-structured artifacts

Build robust, reproducible ELT pipelines in a cloud data stack to generate clean, longitudinal patient-level datasets

Apply OCR and NLP techniques to extract structured signals from unstructured clinical documents

Implement data quality frameworks, testing, version control, and CI/CD for all ingestion and transformation workflows

Collaborate with data science and product partners to ensure data models support causal inference and predictive analysis needs

Optimize pipeline performance and scalability in cloud data warehouses such as Snowflake or comparable technologies

Produce clear documentation and operational runbooks that enable internal consumers to trust and act on healthcare datasets

What you bring to the table

5+ years in Data Engineering, preferably in healthcare, health tech, or regulated domains

Deep SQL skills and Python experience applied to data extraction, transformation, and validation

Experience with dbt or similar transformation tooling and workflow orchestration (Airflow, Argo, etc.)

Proven ability to handle semi-structured and unstructured data common in clinical workflows

Hands-on experience with cloud data platforms (Snowflake, Big Query, Redshift) and scalable pipeline architectures

Strong data modeling skills, especially for longitudinal patient, event, and lab data structures

Clear communicator comfortable explaining technical decisions to both technical and non-technical stakeholders

Bonus if you have

Familiarity with healthcare standards like FHIR, HL7, or clinical interoperability frameworks

Practical experience with OCR/NLP libraries for document parsing in a data pipeline

Exposure to predictive analytics or ML model feature engineering in clinical contexts

Exposure to building data assets that support causal inference or observational research

Previous mentorship or leadership experience within data engineering teams

What we can offer you

Salary range: $140,00 to $160,000 CAD

Flexible PTO and competitive pay, because work-life balance matters

RRSP/401k match and stock options to invest in your future

Premium benefits package with customizable coverage, paramedical services, and an HSA.

Fullscript discounts to save on high-quality wellness products

Continuous learning opportunities to grow your skills and career

Remote-first flexibility to work where you work best, with Ottawa, Toronto, or Calgary preferred for…