Databricks Architect

Data Architect – Databricks

Location: Hybrid – Dallas, TX | Chicago, IL | Atlanta, GA | Charlotte, NC | Minnesota | Cupertino, CA | San Francisco, CA Experience: 10+ Years

Job Summary

Seeking an experienced Data Product Architect / Databricks Architect to lead the design and implementation of enterprise Data Product standards, architecture patterns, governance practices, and engineering frameworks within the Databricks Lakehouse ecosystem.

The ideal candidate will have strong hands-on experience with Databricks, Delta Lake, Unity Catalog, Spark, Python, SQL, cloud platforms, Data Mesh, Data Products, data governance, and enterprise data architecture.

This role will combine hands-on architecture and MVP development with technical leadership, stakeholder engagement, architecture workshops, and consulting.

Key Responsibilities

• Lead the design and implementation of enterprise Data Product standards, architecture patterns, and engineering practices within Databricks.
• Partner with business stakeholders, Risk teams, Data Product Owners, and technology leadership to identify high-value data products.
• Define reusable Data Product frameworks, reference architectures, governance controls, metadata standards, and quality requirements.
• Architect and build end-to-end MVP Data Products using Databricks.
• Design data ingestion, transformation, quality, metadata, security, lineage, and consumption layers.
• Develop scalable Lakehouse solutions using Databricks, Delta Lake, Unity Catalog, Spark, and cloud-native services.
• Establish delivery standards supporting product-based data management and domain-oriented ownership.
• Design reusable data product templates, CI/CD patterns, monitoring, observability, and automated testing frameworks.
• Evaluate existing data assets and technology capabilities to identify modernization opportunities.
• Build proof-of-value demonstrations and working MVPs to validate architecture and business value.
• Lead technical workshops, architecture reviews, and discussions around data contracts, interoperability, discoverability, and consumption patterns.
• Provide technical leadership and mentorship to engineering teams.
• Support solution architecture, proposals, effort estimation, and client presentations for Databricks and Data Product transformation initiatives.

Basic Qualifications

• 10+ years of experience in Data Engineering, Data Architecture, Analytics Engineering, or Enterprise Data Management.
• 5+ years designing and implementing modern cloud-based data platforms and data products.
• 4+ years hands-on Databricks experience, including: Delta Lake, Unity Catalog, Databricks Workflows, MLflow, Lakehouse Architecture.
• 5+ years designing scalable data architectures and distributed data processing solutions.
• 4+ years building enterprise data pipelines using Spark, Python, SQL, and cloud-native technologies.
• 3+ years implementing Data Product operating models, Data Mesh concepts, domain-driven data ownership, or product-oriented data delivery.
• 3+ years delivering cloud solutions using Azure, AWS, or GCP.
• Strong experience with data governance, metadata management, data quality, lineage, and security controls.
• Experience creating reusable architecture patterns, engineering standards, and platform accelerators.
• Experience translating business requirements into scalable data product solutions.
• Strong communication and consulting skills with the ability to lead technical workshops and architecture discussions.

Preferred / Additional Skills

• Data Mesh and domain-driven architecture
• Data Contracts
• Data Product lifecycle management
• Enterprise Data Governance
• Data Quality & Observability
• CI/CD and DevOps
• Cloud Data Architecture
• Risk / Banking data domain experience