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
Information Technology
Lead design and implementation of scalable Databricks Lakehouse solutions using Delta Lake, Unity Catalog, and MLflow. Advise stakeholders, drive cloud data platform modernization across Azure/AWS/GCP, ensure data governance and quality, optimize performance and cost, and mentor teams. Support presales, deliver billable consulting, and champion AI/ML-enabled data solutions to translate platform capabilities into business outcomes.
Top Skills:
AWSAzureBatch StreamingData CatalogingData GovernanceData LineageDatabricksDelta LakeEltETLGCPMaster Data ManagementMlflowPysparkPythonRbacScalaSQLUnity Catalog
Logistics • Real Estate • Energy • Utilities
Lead architecture and technical delivery of a Databricks Lakehouse platform on Azure. Define end-to-end architecture, implement scalable Databricks patterns, migrate use cases to production, enforce governance/security (Unity Catalog, RLS, encryption), design streaming/batch pipelines, mentor engineers, and drive standards, observability, and reusable IaC assets to support analytics and AI/ML workloads.
Top Skills:
Ai GatewaySparkAuto LoaderAzure IdentityAzure NetworkingAzure SecurityAzure StorageCassandraCi/CdDatabricksDatabricks LakehouseDelta LakeDelta Live Tables (Dlt)GenaiHadoopMedallion ArchitectureAzureModel ServingObservability/MonitoringPysparkPythonSQLStructured StreamingTerraformUnity CatalogVector Search
Information Technology • Database • Consulting
Lead architecture and design of enterprise Azure data platforms centered on Databricks Lakehouse. Define ingestion, transformation, and serving layers; implement PySpark/SQL ETL/ELT, Delta Lake patterns, governance with Unity Catalog and Purview, Spark performance tuning, CI/CD, and provide technical leadership and delivery governance across teams.
Top Skills:
AbacAuto LoaderAzure Data FactoryAzure Data Lake StorageAzure DevopsAzure Key VaultAzure PurviewDatabricksDatabricks ServerlessDatabricks WorkflowsDelta LakeDelta Live TablesLakehouse FederationPhotonPysparkPythonRbacSparkSQLUnity Catalog
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
