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, MNWork Arrangement: Onsite / HybridSummaryWe 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.ResponsibilitiesDesign and develop full stack web applications for data ingestion, management, visualization, and labelingBuild and maintain backend services and REST APIs to support data workflowsDesign and implement data pipelines for ingesting, transforming, and storing large datasetsIntegrate data from multiple external systems and sourcesSupport longitudinal data tracking and versioning across datasetsCollaborate closely with data scientists, R&D engineers, and domain expertsEnsure performance, reliability, and maintainability of the platformFollow best practices for data security, privacy, and complianceRequired Skills & QualificationsFull Stack DevelopmentStrong 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 architectureData EngineeringExperience designing and building data pipelines (ETL/ELT)Strong data modeling skillsExperience with PostgreSQL and NoSQL databasesFamiliarity with cloud based data storage and compute (Azure preferred)Preferred / Nice to Have SkillsExperience working with large imaging and time series datasetsExposure to healthcare, clinical, or regulated data environmentsFamiliarity with data anonymization or pseudonymization techniquesExperience supporting ML/AI data preparation workflowsDevOps experience (CI/CD pipelines, containerization)Deliverables & ExpectationsScalable and reliable data ingestion and management capabilitiesWell documented, production quality codeImproved support for longitudinal and multi source data workflowsClose collaboration with internal teams to meet project timelines