Data Architect

Role Overview

• Define and maintain KSM’s Databricks lakehouse architecture, including ingestion, storage, transformation, modeling, and access patterns
• Establish clear, repeatable design standards for Bronze, Silver, and Gold data layers to ensure consistency and reuse
• Design architecture that supports structured, semi-structured, and unstructured data across enterprise systems
• Design and implement data governance, lineage, and quality frameworks that ensure data is trusted, auditable, and scalable
• Enable discoverability, access control, and metadata management using Databricks Unity Catalog and related tooling
• Partner with data and analytics teams to define validation standards, reconciliation processes, and ownership models
• Partner closely with the Senior Data Engineer to translate architectural standards into production-ready pipelines
• Review and validate data pipelines, models, and workflows to ensure alignment with architectural best practices
• Support teams by providing guidance, patterns, and examples rather than one-off solutions
• Define best practices for Databricks compute and storage optimization, balancing performance and cost
• Establish architectural patterns that promote reliability, scalability, and operational simplicity
• Collaborate on monitoring, alerting, and operational standards to ensure platform health
• Define and support CI/CD standards for data pipelines and lakehouse infrastructure
• Partner with engineering teams to implement Infrastructure as Code (IaC) using tools such as Terraform
• Ensure consistent, automated deployments across development, test, and production environments
• Align data architecture decisions with firm-wide analytics, automation, and AI strategy
• Help prioritize architectural investments that deliver near-term value while supporting long-term growth
• Evaluate emerging data platform capabilities thoughtfully, focusing on practical adoption rather than experimentation for its own sake.

Requirements

• 7+ years of experience in data architecture, data engineering, or enterprise data platform design
• Proven experience designing and implementing Databricks or similar modern lakehouse architectures
• Strong understanding of modern data architecture patterns, including medallion architecture and real-time or near-real-time data processing
• Deep expertise in data modeling (conceptual, logical, and physical) for analytics and BI use cases
• Hands-on experience with SQL, Python, and PySpark
• Experience implementing data governance, lineage, and quality frameworks
• Familiarity with Power BI or similar BI and analytics tools
• Strong collaboration skills with the ability to work effectively across technical and business teams
• Excellent communication and documentation skills, with the ability to clearly explain architectural decisions.

Tech Stack

• PySpark
• Python
• SQL
• Terraform
• Unity

Benefits

• flexibility to manage your time
• resources to grow
• team that genuinely cares about your success