Position: Senior Data Engineer / Data Architect at Cactus Companies. Location: Piney Point Village, Texas, United States (Hybrid work arrangement: in office 4 days per week, remote 1 day).

Summary: The Senior Data Engineer / Data Architect is responsible for designing, building, and governing the enterprise data platform on Azure Databricks. This role combines hands-on data engineering delivery with data architecture design to ensure data is reliable, scalable, secure, and ready to support analytics, reporting, and AI initiatives. The role transforms data from ERP, CRM, and other enterprise systems into trusted, reusable data products to enable business insights and future AI capabilities.

Key responsibilities: - Data Engineering & Pipeline Development: design and build end-to-end data pipelines (batch and near real-time) using Databricks and Spark; implement and maintain Bronze/Silver/Gold data architecture layers; ingest data from ERP, SaaS applications, APIs, and legacy systems into Lakehouse; optimize pipelines for performance, scalability, and cost; implement CI/CD pipelines using GitHub. - Data Architecture & Modeling: define and maintain the enterprise data architecture and standards; design logical and physical data models across core business domains (finance, operations, field service); establish consistent definitions for critical entities (customer, job, revenue); ensure data structures support analytics and AI/ML workloads. - Data Governance, Security & Quality: implement and manage Unity Catalog–based governance (RBAC, lineage, auditability); define and enfo

Position: Senior Data Engineer / Data Architect at Cactus Companies. Location: Piney Point Village, Texas, United States (Hybrid work arrangement: in office 4 days per week, remote 1 day).

Summary: The Senior Data Engineer / Data Architect is responsible for designing, building, and governing the enterprise data platform on Azure Databricks. This role combines hands-on data engineering delivery with data architecture design to ensure data is reliable, scalable, secure, and ready to support analytics, reporting, and AI initiatives. The role transforms data from ERP, CRM, and other enterprise systems into trusted, reusable data products to enable business insights and future AI capabilities.

Key responsibilities: - Data Engineering & Pipeline Development: design and build end-to-end data pipelines (batch and near real-time) using Databricks and Spark; implement and maintain Bronze/Silver/Gold data architecture layers; ingest data from ERP, SaaS applications, APIs, and legacy systems into Lakehouse; optimize pipelines for performance, scalability, and cost; implement CI/CD pipelines using GitHub. - Data Architecture & Modeling: define and maintain the enterprise data architecture and standards; design logical and physical data models across core business domains (finance, operations, field service); establish consistent definitions for critical entities (customer, job, revenue); ensure data structures support analytics and AI/ML workloads. - Data Governance, Security & Quality: implement and manage Unity Catalog–based governance (RBAC, lineage, auditability); define and enfo