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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, BigQuery, 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: $110,00 to $140,000 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 this role.
Fullscript shares salary ranges to support transparency and help candidates make informed decisions. The range shown reflects base salary only and does not include stock options, wellness stipends, or other benefits that are part of Fullscript’s total rewards package.
Final compensation depends on experience, skills, and location. We review pay regularly to stay aligned with market data and internal equity. Benefits and total rewards may vary by region.
Why Fullscript
Great work happens when people feel supported, trusted, and inspired. At Fullscript, we stay curious and keep finding smarter ways to make care better. We grow together, take on new challenges, and focus on impact. We put people first, work as a team, and leave egos at the door.
What to Know Before You Apply
We’re grateful for the interest in joining Fullscript. To make sure your application reaches our hiring team, please apply directly through our careers page.
A quick note: Due to the high volume of applications, we’re not able to respond to phone or email inquiries about application status. If there’s a match, our team will reach out directly.
A quick note: Due to the high volume of applications, we’re not able to respond to phone or email inquiries about application status. If there’s a match, our team will reach out directly.
Fullscript is an equal opportunity employer committed to creating an inclusive workplace. Accommodations are available upon request at [email protected].
All offers are contingent on successful background checks conducted in compliance with federal, state, and provincial laws.
We use AI tools to support parts of the hiring process, including screening and reviewing responses. Final hiring decisions are always made by people and follow all applicable privacy and employment laws in Canada and the U.S.
Learn More
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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