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Tier-1 brand, mid-level generalist Data/AI role in metro with broad Azure/ML requirements.
Role needs specialized cloud data platform and MLOps experience, transferable but requires domain-specific skills.
Explicit 5+ years requirement plus mandatory Azure, Databricks, ML and MLOps skills makes filtering strict.
Own end-to-end design, development, deployment, and maintenance of scalable data pipelines and AI/ML solutions on Azure cloud platforms.
Build and operationalize robust ETL/ELT pipelines and integrate LLM-based generative AI models including RAG pipelines for business applications.
Collaborate cross-functionally with business stakeholders, data scientists, and technical teams to translate requirements into production-ready AI features delivering measurable business impact.
5+ years of combined experience in data engineering and AI/ML engineering with focus on Azure data and AI platforms.
Proficiency in Azure Data Factory, Azure Data Lake, Azure Databricks, Azure Machine Learning, and Azure OpenAI Service.
Strong skills in SQL, Python, PySpark, and experience with ML frameworks like PyTorch, TensorFlow, or scikit-learn.
Graduate or postgraduate degree in Computer Science, IT, Data Engineering, AI, Data Science, or related field.
Experienced in managing full data-to-AI lifecycle with proven ability to build scalable cloud data and AI platforms using Microsoft Azure stack.
Capable of working in Agile/DevOps environments with end-to-end ownership including automation, CI/CD, and MLOps best practices.
Comfortable engaging with diverse stakeholders to design and deliver complex data and AI solutions translating business needs into technical implementations.