Databricks Architect
Location: United States
Department: MLE
Workplace: remote
Description
Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.
This role will be responsible for Databricks Architecture, Designing and implementing best data practices.
Requirements
- Strong Experience inĀ DataĀ Architecture, specifically withĀ Databricks Architecture.
- Expert inĀ DatabricksĀ Lakehouse (Delta Lake, Unity Catalog, MLflow), AWS, Snowflake, and Apache Iceberg.
- Strong MLOps & CI/CD Expertise
- Proficient in Python/Scala (Spark) forĀ dataĀ governance, security, and enterpriseĀ dataĀ platform design.
- DatabricksĀ certifications and GenAI architecture experience preferred.
Key Responsibilities:
- Architect and strategizeĀ DatabricksĀ on AWS/Snowflake integration for secure, scalableĀ data/AI platforms.
- Architect seamless Snowflake/DatabricksĀ dataĀ flow via Apache Iceberg (including ML output).
- Design cost-managed multi-regionĀ DatabricksĀ MLOps platform andĀ dataĀ flows.
- Implement Unity Catalog for fine-grained access control and secure team coexistence with Workspaces.
- DevelopĀ Databricks-native MLOps (environment parity, Git-driven CI/CD, governed access, MLflow governance, standardized deployment, monitoring).
- Define enterprise-scalable AI governance for GenAI production deployment.
Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
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