Senior Data Engineer owning NimbleRx’s compliant healthcare data platform. Building scalable pipelines, warehouse models, and AI tooling for pharmacy and patient engagement operations.
About the role
- Data Engineer building scalable Databricks ingestion pipelines for Irth Solutions’ infrastructure-protection SaaS. Supporting stakeholder-engagement analytics, LLM/NLP pipelines, and downstream data models.
Responsibilities
- Design, build, and maintain ingestion pipelines from high-volume external APIs that run continuously and reliably at scale
- Implement ingestion and transformation workflows in Databricks using Spark/PySpark, SQL, and Delta Live Tables
- Apply medallion architecture patterns from raw content to clean, structured, analysis-ready data
- Build deduplication and relevance-filtering infrastructure in collaboration with the Data Scientist
- Implement schema evolution handling and data validation rules
- Configure and manage Delta Lake storage structures, tables, partitions, and optimization routines
- Design and evolve data schemas balancing query performance, cost, and maintainability
- Maintain metadata and table-structure documentation for Data Science and application teams
- Ensure pipeline reliability and observability through error handling, retries, monitoring, and alerting
- Adapt pipelines to changing external API contracts, rate limits, authentication methods, and new data sources
- Troubleshoot pipeline failures, perform recovery, and tune performance
- Build, schedule, and monitor workflows using Databricks Workflows, Delta Live Tables, or similar tools
- Contribute to CI/CD pipelines for code deployment, versioning, and environment management
- Collaborate with the Data Scientist to provide structured data for LLM/NLP pipelines and downstream models
- Participate in data-architecture decisions and propose solutions as team needs evolve
- Document pipelines, data dictionaries, job schedules, and transformation logic
- Support onboarding of new data sources and pipelines as the product expands
Requirements
- Strong preference for candidates residing in Quebec
- Fluency in French (spoken and written) is a strong asset in addition to English
- 3 to 5 years of experience in data engineering, with solid experience building and operating production-grade data pipelines
- Familiarity with data modeling, data quality, and schema evolution
- Solid understanding of data pipeline reliability practices: monitoring, alerting, and handling failures gracefully in a continuously running system
- Hands-on experience with Databricks or an equivalent Spark-based environment, including schema design, Delta Lake, performance tuning, and pipeline orchestration
- Experience with at least one major cloud provider; Azure preferred, AWS/GCP also beneficial
- Experience integrating with external APIs at scale, including authentication, pagination, rate limiting, retries, and error handling
- Strong proficiency in Python and SQL
- Comfortable working with unstructured/semi-structured text data at scale
- LLM prompting experience and/or basic understanding of AI/NLP concepts
- Exposure to medallion architecture or lakehouse best practices
- Experience with orchestration frameworks such as ADF, Workflows, Airflow, or DBX
- Experience with CI/CD tools and version control, such as Git or GitHub Actions
- Basic understanding of security practices, including RBAC, encryption, and credential management
- Databricks certification (Data Engineer Associate or equivalent)
Benefits
- Competitive compensation package based on experience and qualifications
- Medical, Dental, and Vision Insurance
- 401(k) Plan with Company Match
- Generous Paid Time Off (PTO)
- Company-Paid Holidays
- Flexible Work Options / Work-from-home opportunities
- On-Call Compensation — Additional pay for eligible on-call shifts
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