Databricks Architect

Tiger Analytics Inc.; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

Tiger Analytics Inc. is seeking a skilled professional for Databricks Architecture. The role involves designing and implementing best data practices within a dynamic environment.

The ideal candidate will bring strong expertise in Data Architecture with a focus on Databricks, MLOps, and secure data platforms. This position offers significant career development opportunities in a fast-growing entrepreneurial setting.

Qualifications

• Strong experience in Data Architecture, specifically with Databricks.
• Expertise in Databricks Lakehouse (Delta Lake, Unity Catalog, MLflow) and MLOps.
• Proficient in Python/Scala (Spark) for data governance and enterprise data platforms.

Responsibilities

• Architect and strategize Databricks on AWS/Snowflake integration.
• Design seamless Snowflake/Databricks dataflow via Apache Iceberg.
• Implement Unity Catalog for secure team coexistence.

Skills

Data Architecture

Databricks Lakehouse

MLOps

Python/Scala (Spark)

Education

Databricks certifications

Tools

AWS

Snowflake

Apache Iceberg

Job 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 in Data Architecture, specifically with Databricks Architecture.
• Expert in Databricks Lakehouse (Delta Lake, Unity Catalog, MLflow), AWS, Snowflake, and Apache Iceberg.
• Strong MLOps & CI/CD Expertise
• Proficient in Python/Scala (Spark) for data governance, security, and enterprise data platform design.
• Databricks certifications and GenAI architecture experience preferred.

Key Responsibilities

• Architect and strategize Databricks on AWS/Snowflake integration for secure, scalable data/AI platforms.
• Architect seamless Snowflake/Databricks dataflow via Apache Iceberg (including ML output).
• Design cost-managed multi-region Databricks MLOps platform and dataflows.
• Implement Unity Catalog for fine‑grained access control and secure team coexistence with Workspaces.
• Develop 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.