Full Stack Data Engineer

About the Role
The Data Engineering team plays a pivotal role in creating, maintaining and developing BioIntelliSense’s data platform for both internal and external facing applications. The team focuses on enterprise data management and data accuracy to support internal operations, R&D teams as well as external operational metrics dashboards. In this role, you will have the opportunity to collaborate with cross-functional teams such as clinical applications, cloud infrastructure, sustaining, and data science, building your analytical mindset and the ability to communicate system-level relationships clearly. You will work primarily with the Python tech stack on Databricks and AWS. Your contributions will have a meaningful impact in BioIntelliSense’s mission to improve patient care around the world.
The role will:
Apply strong computer science fundamentals to develop and implement data pipelines and cloud-native applications.
Create highly scalable REST APIs and web applications to support clinical workflows and internal tools.
Design and maintain automated ETL/ELT pipelines to ingest, clean, and transform clinical data from various sources into our internal data environment.
Implement data validation and quality checks to ensure accuracy and reliability in clinical workflows and reporting.
Collaborate with a technical lead, product, and cross-functional teams to implement solutions that will continue to streamline internal operations as well as generate commercial value.
Participate in the engineering on-call rotation to ensure high service availability and uptime.
Apply software development best practices to bring product requirements to commercial deployment.
Allow advancement in career growth tailored to individual goals.
Requirements
Bachelor’s degree in Computer Science or Engineering.
Experience developing software applications, including internships or academic projects.
Strong written and oral communication skills.
Able to work both independently and collaboratively, with a strong capacity to interpret and execute abstract instructions.
Willingness to learn and contribute to product improvements.
Solid knowledge of Python.
Solid understanding of SQL fundamentals, including the ability to perform joins and aggregate data from relational databases.
Preferred
Familiarity with cloud platforms: AWS/GCP.
Familiarity with ETL/ELT pipelines, data transformations and platforms such as Databricks.
Familiarity with Terraform and CI/CD pipelines.