Databricks Architect

Job Description Databricks Architect Must Have Technical/Functional Skills Mandatory Former Databricks Employee (Non-Negotiable Requirement) 12+ Years of IT Experience 5+ Years of Databricks Architecture Experience Strong Lakehouse Architecture Expertise Hands-on Spark/PySpark Experience Enterprise Cloud Data Platform Design Experience Data Governance & Security Expertise Stakeholder Management and Leadership Experience Preferred BFSI Domain Experience GenAI / AI Platform Architecture Experience Large-scale Cloud Migration Experience Pre-sales / Solution Consulting Experience Databricks Technologies Databricks Lakehouse Platform Delta Lake Photon Engine Unity Catalog Delta Live Tables (DLT) Databricks Workflows MLflow Auto Loader Structured Streaming Databricks SQL Databricks Asset Bundles Data Engineering Apache Spark PySpark Spark SQL Scala (preferred) Python SQL Optimization Data Modeling Data Warehousing Cloud Platforms Microsoft Azure (Preferred) Azure Data Factory Azure Synapse Analytics Azure Storage Azure Key Vault Azure Entra ID (Azure AD) OR AWS Databricks Ecosystem Google Cloud Databricks Ecosystem DevOps & Automation Terraform GitHub Azure DevOps CI/CD Pipelines Docker Kubernetes Data Governance & Security Unity Catalog Apache Ranger Data Lineage Tools Data Quality Frameworks Data Classification & Governance ________________________________________ Domain Experi Ence (Preferred) Banking & Financial Services (BFSI) Capital Markets Wealth Management Insurance Lending & Consumer Finance Regulatory Reporting and Compliance ________________________________________ Certifications (Preferred) Databricks Certified Data Engineer Professional Databricks Certified Solution Architect Databricks Certified Machine Learning Professional Azure Solutions Architect Expert Azure Data Engineer Associate Roles & Responsibilities Architecture & Strategy Design and implement enterprise-scale Databricks Lakehouse platforms. Define end-to-end data architecture for batch, streaming, and real-time analytics solutions. Develop cloud-native data platform strategies aligned with business objectives. Establish architectural standards, governance frameworks, and best practices. Lead modernization initiatives involving legacy data warehouse migration to Databricks. Data Engineering & Integration Design scalable ETL/ELT pipelines using Databricks, Apache Spark, and Delta Lake. Build medallion architecture (Bronze, Silver, Gold layers) for enterprise data platforms. Integrate data from multiple sources including databases, APIs, SaaS platforms, and streaming systems. Implement data quality, lineage, observability, and monitoring frameworks. Optimize data ingestion and transformation processes for performance and scalability. Cloud & Platform Engineering Architect Databricks solutions on Azure, AWS, or Google Cloud Platform. Design secure networking, storage, identity management, and access controls. Implement Infrastructure as Code (Terraform, ARM, CloudFormation). Optimize platform usage and cloud costs through governance and monitoring. Lead Databricks workspace design and multi-environment deployment strategies. AI, ML & Advanced Analytics Architect Databricks solutions supporting Machine Learning and Generative AI workloads. Design ML lifecycle management using MLflow. Enable enterprise AI capabilities leveraging Databricks Mosaic AI and GenAI frameworks. Collaborate with Data Scientists and AI teams to operationali ze ML models. Establish MLOps best practices and governance standards. Security & Governance Implement Unity Catalog for enterprise-wide governance. Define data security controls including RBAC, ABAC, encryption, and access management. Ensure compliance with industry standards including SOX, PCI-DSS, HIPAA, GDPR, and BFSI regulatory requirements. Establish data governance, metadata management, and audit frameworks. Leadership & Stakeholder Management Act as the primary Databricks subject matter expert. Engage with executive stakeholders to define data transformation roadmaps. Conduct architecture reviews and provide technical leadership. Mentor data engineers, platform engineers, and architects. Collaborate with business, infrastructure, security, and application teams. Salary Range- $120,000-$150,000 a year