We are seeking an experienced Data Systems Developer who is humble, curious, and insists on high standards. The ideal candidate will possess extensive technical expertise in MySQL, Azure cloud services, and Labelbox, which will help the team efficiently manage and process large volumes of healthcare data, playing a critical role in supporting the development of AI models and applications. Deep Breathe team members must be agile in adapting to the various needs of a small company by learning new skills, adjusting priorities in the case of shifting deadlines, and working directly with software engineers, data scientists, and clinicians.
As a growing team, we value individuals who see challenges as an opportunity for growth and take true ownership of their work. The successful candidate will be instrumental in designing, developing, and maintaining our data infrastructure. Through collaborating closely with data scientists, software engineers, and healthcare professionals, the chosen candidate will ensure the accuracy, integrity, and accessibility of our data systems.
Educational Background and Professional Experience:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 3+ years of experience in data engineering or a similar role
Role Responsibilities/Requirements:
- Design, develop, and maintain scalable data pipelines and ETL processes to ingest, process, and store healthcare data from various sources, ensuring data quality, validation, and integrity.
- Manage and optimize databases, for performance, reliability, and scalability.
- Collaborate with data scientists and machine learning engineers to deliver clean, well-documented datasets suitable for AI model training and evaluation.
- Implement data versioning strategies to track changes, ensure reproducibility, and maintain governance in data workflows.
- Development of testing suite and to ensure integrity of data versioning and data quality
- Utilize cloud infrastructure, primarily Azure, to deploy and manage data solutions, integrating tools like Labelbox for data labeling and annotation.
- Develop and maintain comprehensive documentation for data processes, infrastructure, and usage guidelines.
- Monitor and troubleshoot data pipelines and infrastructure to ensure smooth operation, minimize downtime, and adhere to best practices in data governance and security.
Technical proficiency/experience in the following areas:
- Python (for data manipulation and automation)
- MySQL (as well as other relational databases)
- Labelbox (or similar data labeling platforms)
- Azure cloud services (such as Azure Data Factory, Azure MySQL, and Azure Storage) and/or adjacent cloud computing platforms
- GitHub (or similar code versioning platforms)
Not required, but preferred:
- Experience in the healthcare industry/familiarity with healthcare data standards (e.g., HL7, FHIR).
- Experience developing systems that are compliant with healthcare data privacy regulations such as HIPAA, GDPR, and other related frameworks.
- Knowledge of other cloud platforms such as AWS or Google Cloud.
- Familiarity with containerization and orchestration tools (i.e., Docker and Kubernetes)
- Experience with big data technologies (such as Hadoop, Spark, or Kafka)
40 Hours/week
Hybrid work environment, London, ON
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