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Known consultancy brand, generalist backend role, mid-level experience, metro location increase competition.
Backend engineering skills with cloud and MLOps are transferable across industries but require domain familiarity.
Multiple mandatory tech stack items and cloud/databricks requirements make filtering moderately strict.
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Design, develop, and maintain scalable Python backend services using FastAPI to support large data modeling and statistical/ML models.
Integrate backend services with Azure cloud components, including Azure Data Lake Storage, Databricks Delta Lake, Azure DevOps, and implement secure API authentication and authorization.
Develop, automate, and maintain CI/CD pipelines and support ML flow/MLOps frameworks for model deployment and lifecycle management.
Proficiency in Python backend development with experience in FastAPI framework and REST API design.
Experience integrating backend systems with Azure cloud services, Databricks, and Delta Lake.
Hands-on knowledge of authentication, authorization, modular coding, async programming, and automated testing with pytest.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced backend developer comfortable collaborating with data scientists and business stakeholders to operationalize statistical and machine learning models.
Familiar with Agile delivery, Scrum, Git version control, and DevOps practices within cloud environments.
Capable of producing reusable, maintainable code and participating in architecture planning and technical design discussions.