Databricks Architect
Role details
Job location
Tech stack
Requirements
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Experience in data/ML engineering or architecture
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Hands-on Databricks experience
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Strong expertise in MLOps frameworks and production ML systems
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Deep experience with:
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MLflow
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Python (PySpark, Pandas, scikit-learn)
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Spark-based data processing
Experience designing enterprise-grade data platforms (lakehouse architecture)
Proven ability to deploy ML models into production environments
Preferred Qualifications/ Skills
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Experience in banking or financial services.
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Strong understanding of Model Risk Management (MRM), including:
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Model validation workflows
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Auditability and documentation standards
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Regulatory expectations (SR 11-7, etc.)
Familiarity with:
- Feature stores (Databricks Feature Store)
- Real-time / batch inference patterns
- Data governance and lineage tracking