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Mid-level backend role, metro location, and a generalist, popular title drive high competition.
Core backend, cloud, and data-platform skills are transferable, though Databricks/MLOps add some domain specificity.
Multiple mandatory technologies (FastAPI, Azure, Databricks, MLOps) create high filtering strictness.
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Design, develop, and maintain scalable backend services and RESTful APIs using Python and FastAPI.
Integrate backend services with Azure cloud components including Azure Data Lake Storage, Databricks Delta Lake, and Azure DevOps.
Collaborate with data scientists and business stakeholders to operationalize statistical and machine learning models in production environments.
Proficiency in Python, FastAPI Framework, REST API design, Pydantic models, Async programming.
Experience with Azure cloud, Databricks, Delta Lake, Azure DevOps, and Git versioning.
Experience in developing secure authentication, authorization, and API security mechanisms.
Work Experience Required: Not explicitly mentioned in the JD
Background combining backend development with data science model basics and cloud-based solutions.
Experience working in Agile environments with Scrum, automated testing (pytest), and CI/CD pipeline development.
Ability to collaborate across teams including frontend developers and data scientists to integrate complex data-driven services.