Databricks Architect
Tiger Analytics Inc. Open · verified Oct 24, 2026 At a glance
Mid-level Data Engineering role at Tiger Analytics Inc. Remote, United States · no salary stated · we estimate $112,500–$160,000 across the United States.
Tiger Analytics Inc. has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Plan secure, scalable data and AI platforms connecting Databricks with AWS and Snowflake
- Build data flows between Snowflake and Databricks through Apache Iceberg, including machine-learning outputs
- Design multi-region Databricks MLOps systems and data flows with cost controls
- Set up Unity Catalog permissions so teams can share workspaces securely
- Establish governed GenAI deployment practices and Databricks MLOps workflows for releases and monitoring
What you bring
- You have strong data architecture experience, especially designing Databricks platforms
- You bring expert knowledge of Databricks Lakehouse, AWS, Snowflake and Apache Iceberg
- You are strong in MLOps and CI/CD, with Python or Scala for Spark-based platform work
Who this fits
This mid-level role suits someone focused on Databricks architecture across data, AI governance and MLOps. It is remote within the United States.
From the employer
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 data flow via Apache Iceberg (including ML output).
- Design cost-managed multi-region Databricks MLOps platform and data flows.
- 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.
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