Databricks Architect

Confiz is seeking an experienced Databricks Architect to lead the design, architecture, and delivery of enterprise data platforms that power AI and Business Intelligence solutions. As the technical authority for the Databricks Lakehouse Platform, you will own the end-to-end data architecture-from data discovery and ingestion through governed, secure, and production-ready data products. This role is responsible for establishing scalable data platform standards, driving AI-ready data solutions, and ensuring enterprise security, governance, and compliance through Unity Catalog and modern data protection practices. The ideal candidate brings deep expertise in Databricks, cloud data platforms, enterprise architecture, and data governance while partnering closely with business and engineering teams to deliver innovative AI-driven solutions., * Lead the architecture, design, and delivery of enterprise data platforms supporting AI, analytics, and business intelligence initiatives.

• Design scalable data models, pipelines, and Lakehouse architectures using Databricks, Delta Lake, and Medallion Architecture.
• Translate business requirements into secure, scalable data solutions that support AI, BI, and natural language query experiences.
• Establish standards for data quality, governance, lineage, observability, and reusable architecture patterns.
• Facilitate data discovery sessions with business stakeholders to identify, assess, and validate enterprise data sources.
• Evaluate data readiness, identify gaps, and develop remediation plans in partnership with data engineering and business teams.
• Architect the Databricks platform, including workspace strategy, compute, storage, networking, CI/CD, and infrastructure-as-code deployment practices.
• Optimize platform performance, scalability, and cost across Databricks clusters, SQL Warehouses, and serverless environments.
• Own platform security architecture, including identity integration, secrets management, network security, and access controls.
• Design and implement Unity Catalog governance, metadata management, lineage, row- and column-level security, dynamic data masking, and attribute-based access controls.
• Develop enterprise strategies for PII classification, masking, and protection across AI and conversational analytics solutions.
• Partner with Security, Privacy, and Compliance teams to ensure regulatory and audit requirements are met.
• Provide technical leadership, architecture reviews, and mentorship to Data Engineers and cross-functional teams.
• Stay current on emerging Databricks capabilities and recommend adoption of new platform features and best practices., We have a global team of amazing individuals working on highly innovative enterprise projects & products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast growth fintech, and multiple Silicon Valley startups.

What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM) and ISO 14001:2015 (EMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.

People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field.
• 8+ years of experience in Data Architecture or Data Engineering, including 3+ years architecting enterprise Databricks solutions.
• Deep expertise with the Databricks Lakehouse Platform, including Delta Lake, Unity Catalog, Databricks SQL, Workflows, and Medallion Architecture.
• Strong experience designing enterprise data governance and security frameworks, including Unity Catalog governance, row- and column-level security, data masking, and least-privilege access models.
• Hands-on experience implementing PII classification, protection, and governance strategies for AI, analytics, or natural language query platforms.
• Advanced proficiency with SQL and Python (PySpark).
• Strong data modeling experience, including dimensional modeling, Data Vault, or domain-driven design.
• Experience with Azure, AWS, or Google Cloud Platform, including networking, identity management, and cloud storage services.
• Proven ability to facilitate discovery workshops and translate business requirements into scalable data architecture solutions.
• Excellent communication, stakeholder management, and technical leadership skills.