Full Stack Developer - Data Engineering

Job Title:

Full Stack Developer (with Data Engineering Experience)

Duration:

Long term (6-12 months, with possible extension)

Location:

Little Canada, MN Work Arrangement:

Onsite / Hybrid Summary We are seeking a FullStack Developer with strong experience in backend development using C#/.NET and frontend development using Angular, along with solid data engineering skills. This role will support the development and enhancement of a data platform used for ingesting, managing, and analyzing largescale imaging and electrophysiology procedural datasets. The ideal candidate is hands on across the full stack and comfortable working with data pipelines, APIs, and scalable enterprise systems. Responsibilities Design and develop full stack web applications for data ingestion, management, visualization, and labeling Build and maintain backend services and REST APIs to support data workflows Design and implement data pipelines for ingesting, transforming, and storing large datasets Integrate data from multiple external systems and sources Support longitudinal data tracking and versioning across datasets Collaborate closely with data scientists, R D engineers, and domain experts Ensure performance, reliability, and maintainability of the platform Follow best practices for data security, privacy, and compliance Required Skills & Qualifications Full Stack Development Strong experience in full stack development (frontend and backend) Strong experience with C# and .NET (.NET Core / .NET Framework)

Frontend:

Strong experience with Angular (TypeScript, HTML, CSS) Experience with RESTful APIs and microservices architecture Data Engineering Experience designing and building data pipelines (ETL/ELT) Strong data modeling skills Experience with PostgreSQL and NoSQL databases Familiarity with cloud based data storage and compute (Azure preferred) Preferred / Nice to Have Skills Experience working with large imaging and time series datasets Exposure to healthcare, clinical, or regulated data environments Familiarity with data anonymization or pseudonymization techniques Experience supporting ML/AI data preparation workflows DevOps experience (CI/CD pipelines, containerization) Deliverables & Expectations Scalable and reliable data ingestion and management capabilities Well documented, production quality code Improved support for longitudinal and multi source data workflows Close collaboration with internal teams to meet project timelines #LI-MS1