Ocean Blue Solution
Role
Data Architect with Databricks
Location Remote.
Required Skills & Experience
Bachelors or Masters degree in Computer Science, Data Engineering, Data Science, or related field.
13 years of experience in data engineering, cloud platforms, or data architecture roles.
3 years of hands‑on experience with Databricks, including Delta Lake, MLflow, Workflows, and SQL/PySpark.
Strong knowledge of Azure, AWS, or Google Cloud Platform cloud services and data ecosystem tools.
Proven experience designing scalable data lake/data warehouse solutions.
Expertise in Python, SQL, and PySpark for large‑scale distributed data processing.
Strong understanding of MLOps principles and ML lifecycle management.
Excellent communication and client‑facing consulting skills.
Ability to lead solution design discussions and document architectures clearly.
Preferred Qualifications
Databricks certifications (e.g., Databricks Certified Data Engineer/Architect, ML Professional).
Experience with Unity Catalog, Feature Store, Model Serving, and Lakehouse AI features.
Familiarity with Terraform, Kubernetes, CI/CD pipelines (GitHub Actions, Azure DevOps, etc.).
Experience working with enterprise clients in consulting, professional services, or SI environments.
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Location Remote.
Required Skills & Experience
Bachelors or Masters degree in Computer Science, Data Engineering, Data Science, or related field.
13 years of experience in data engineering, cloud platforms, or data architecture roles.
3 years of hands‑on experience with Databricks, including Delta Lake, MLflow, Workflows, and SQL/PySpark.
Strong knowledge of Azure, AWS, or Google Cloud Platform cloud services and data ecosystem tools.
Proven experience designing scalable data lake/data warehouse solutions.
Expertise in Python, SQL, and PySpark for large‑scale distributed data processing.
Strong understanding of MLOps principles and ML lifecycle management.
Excellent communication and client‑facing consulting skills.
Ability to lead solution design discussions and document architectures clearly.
Preferred Qualifications
Databricks certifications (e.g., Databricks Certified Data Engineer/Architect, ML Professional).
Experience with Unity Catalog, Feature Store, Model Serving, and Lakehouse AI features.
Familiarity with Terraform, Kubernetes, CI/CD pipelines (GitHub Actions, Azure DevOps, etc.).
Experience working with enterprise clients in consulting, professional services, or SI environments.
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