Database Warehouse Architect

Job Title - Database Warehouse Architect (Fractional) Work Mode- Dallas/Fort Worth/Austin (Texas) Job Description We are seeking a senior, solution-oriented Data Warehousing & Lakehouse Architect to engage on an on-demand consulting basis. This role is designed for an expert who stays current with modern data warehousing trends and has deep hands-on expertise in Databricks-led lakehouse architectures. The consultant will advise on architecture, design scalable data platforms, lead solution discovery, and guide engineering teams. This is not a full-time or staff-augmentation role; it is a high-impact advisory and solution-architecture engagement focused on clarity, correctness, and execution readiness. Required Experience • Senior-level experience in Data Warehousing and Lakehouse Architecture.Deep, hands-on expertise with Databricks (Apache Spark, Delta Lake, Lakehouse patterns). • Strong experience designing cloud-native data platforms on AWS, Azure, or GCP. • Solid understanding of modern data warehousing trends, including: • Lakehouse architectures • Open table formats (Delta Lake, Iceberg, Hudi) • Decoupled storage & compute • Cost and performance optimization strategies • Strong knowledge of ETL/ELT pipelines, SQL, and analytical data modeling. • Experience with data governance, security, metadata, and access controls. • Ability to work independently and provide high-quality architectural guidance on demand. • Strong communication skills with a solution-first, advisory mindset. Responsibilties • Provide on-demand architectural leadership for data warehousing and lakehouse initiatives. • Design and review modern lakehouse architectures with Databricks at the core. • Translate business, analytics, and AI requirements into scalable, cost-efficient data • solutions. • Lead architecture discovery sessions and solution design workshops. • Define best practices for data ingestion, transformation, and modeling (ETL/ELT). • Guide implementation of Databricks (Spark, Delta Lake, Unity Catalog) and Snowflake where applicable. • Ensure data quality, governance, security, and performance optimization. • Perform architecture reviews, feasibility assessments, and modernization recommendations. • Advise teams on data platform choices, trade-offs, and long-term scalability. • Collaborate with data engineers, analytics teams, and stakeholders in a consultative • advisory capacity. • Stay ahead of emerging data warehousing and lakehouse trends, recommending • practical adoption paths Preferred Certifications • Databricks Certified Professional (highly preferred) • Cloud Certification (AWS, Azure, or GCP) • Snowflake Certification – nice to have Nice To Have • Experience with streaming / real-time data architectures. • Exposure to BI and analytics platforms (Power BI, Tableau, Looker). • Experience supporting AI / ML and GenAI workloads on Databricks. • Prior consulting or fractional architect experience. • What This Role Is (and Is Not) • This role is: • On-demand, flexible, and outcome-driven • Architecture and solution focused • Ideal for senior consultants or fractional architects • This role is not: • A full-time employment role • A pure data engineering or operations role • A staff-augmentation position Show more Show less

Senior-level experience in Data Warehousing and Lakehouse Architecture with deep, hands-on expertise in Databricks (Apache Spark, Delta Lake, Lakehouse patterns). Strong experience designing cloud-native data platforms on AWS, Azure, or GCP. Solid understanding of modern data warehousing trends (Lakehouse architectures, open table formats such as Delta Lake, Iceberg, Hudi; decoupled storage & compute; cost and performance optimization). Proficiency in ETL/ELT pipelines, SQL, and analytical data modeling. Experience with data governance, security, metadata, and access controls. Ability to work independently and provide high-quality architectural guidance on demand. Strong communication skills with a solution-first, advisory mindset.

Provide on-demand architectural leadership for data warehousing and lakehouse initiatives. Design and review modern lakehouse architectures with Databricks at the core. Translate business, analytics, and AI requirements into scalable, cost-efficient data solutions. Lead architecture discovery sessions and solution design workshops. Define best practices for data ingestion, transformation, and modeling (ETL/ELT). Guide implementation of Databricks (Spark, Delta Lake, Unity Catalog) and Snowflake where applicable. Ensure data quality, governance, security, and performance optimization. Perform architecture reviews, feasibility assessments, and modernization recommendations. Advise teams on data platform choices, trade-offs, and long-term scalability. Collaborate with data engineers, analytics teams, and stakeholders in a consultative advisory capacity. Stay ahead of emerging data warehousing and lakehouse trends, recommending practical adoption paths.