The Databricks Architect will design and implement data architecture solutions using Databricks, AWS, and Snowflake, focusing on MLOps and data governance.
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.
#LI-remote
Similar Jobs
Big Data • Analytics • Business Intelligence • Big Data Analytics
The Databricks Architect will design and implement large-scale data solutions, optimizing performance and reliability, while leading initiatives in data engineering.
Top Skills:
AWSDatabricksHadoopSpark
Information Technology
The Databricks Solutions Architect leads technical presales, designs scalable Data and AI architectures, and mentors teams on modern data solutions.
Top Skills:
AWSAzureDatabricksDelta Live TablesGCPGenaiGitHadoopKafkaLakeflowSparkTerraformUnity Catalog
Big Data • Analytics • Business Intelligence • Big Data Analytics
The Azure Databricks Senior Architect will be responsible for architecture, design, and implementation of data practices on Azure, focusing on end-to-end data management principles and governance.
Top Skills:
AzureAzure Device Provisioning ServicesAzure Device SdkAzure Device TwinsAzure FunctionsAzure HubAzure Stream AnalyticsBiCosmos DbDatabricksEdw
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
