Senior Data Warehouse Engineer

Location:
Hybrid in Richardson, TX

A confidential financial services organization is seeking a Senior Data Engineering Architect to lead the design and evolution of a modern enterprise data platform. This is a highly strategic, hands‑on leadership role focused on building scalable cloud‑native data solutions with Snowflake and dbt at the center of the architecture.

The ideal candidate will bring deep expertise in Snowflake, dbt, SQL, and enterprise ELT architecture, along with experience establishing engineering standards, driving automation, and mentoring senior data engineering teams. This individual will influence platform strategy, data governance, performance optimization, and CI/CD best practices across a large‑scale analytics ecosystem.

• Lead the architecture, design, and implementation of enterprise ELT pipelines using Snowflake and dbt.
• Build scalable data models across staging, intermediate, and mart layers to support analytics, reporting, and business intelligence initiatives.
• Establish and enforce dbt engineering standards, including reusable macros, testing frameworks, documentation, lineage, and release governance.
• Design and optimize Snowflake architecture, including warehouse strategy, workload isolation, clustering, security, access controls, and cost management.
• Develop enterprise standards for SQL, Python, and PySpark data engineering workloads.
• Implement Infrastructure as Code (Terraform) to manage Snowflake objects and supporting cloud infrastructure.
• Build and govern CI/CD pipelines for dbt deployments, automated testing, validation, and environment promotion.
• Oversee ingestion and data movement processes, ensuring schema evolution handling, reliability, and production‑grade SLAs.
• Define best practices for data quality, observability, monitoring, and operational excellence.
• Partner with platform, security, and compliance teams to ensure enterprise‑grade governance and regulatory alignment.
• Mentor senior and mid‑level data engineers and provide architectural leadership across cross‑functional initiatives.

• 8+ years of experience in data engineering, analytics engineering, or data platform architecture.
• Expert‑level experience with Snowflake in enterprise production environments.
• Extensive hands‑on experience with dbt, including model design, macros, testing, documentation, and deployment workflows.
• Advanced proficiency in SQL for large‑scale data transformation and optimization.
• Experience with Terraform or other Infrastructure as Code frameworks.
• Knowledge of CI/CD practices for data engineering assets.
• Experience leading architecture reviews, establishing standards, and driving enterprise‑wide data engineering best practices.
• Excellent communication and stakeholder management skills.

• Experience in financial services, banking, fintech, or other regulated industries.
• Familiarity with Fivetran, Kafka, and AWS data services.
• Experience supporting streaming or hybrid data processing architectures.
• Background in data governance, lineage, and enterprise metadata management.

• Senior‑level strategic impact on a rapidly evolving enterprise data platform.
• Opportunity to shape Snowflake and dbt standards across the organization.
• High visibility with architecture, analytics, platform, and executive stakeholders.
• Strong focus on modern data engineering, automation, and cloud‑native best practices.
• Collaborative environment with significant opportunities for technical leadership and long‑term career growth.