Principal AI & Data Platforms Engineer

At Guild, we believe talent is everywhere and that opportunity should be too. We continue to have our home and headquarters in Denver, but we have embraced a distributed model of working to reach the best talent in the United States. While some roles may require proximity to our Denver office, roles based outside of our Denver office can sit in any of the following 32 states: AZ, CA, CO, CT, FL, GA, ID, IL, IN, KS, MA, MD, ME, MI, MN, MO, NC, NH, NJ, NV, NY, OH, OK, OR, PA, SC, TN, TX, UT, VA, WA, WI and Washington D.C. Please only apply if you are able to live and work full-time in one of the states listed above. State locations and specifics are subject to change as our hiring requirements shift. 

If you are an Internal Candidate, please apply via our Internal Job Board. 

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To thrive as a company and meet our impact goals, we must cultivate a culture of high-performance. We know managers are often the single-largest driver of employee satisfaction and growth, and our talent is our biggest asset. Because of that, we’ve identified consistent expectations for all of Guild’s people managers — helping you know what to expect from your experience here.

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As a Principal Data Engineer, you will lead technical strategy and execution for our robust, scalable, and modern data ecosystem. You'll collaborate cross-functionally with data analysts, engineering teams, and business stakeholders to architect sophisticated data solutions powering analytics, operational insights, and innovative products.

This high-impact role is designed for an experienced technical leader who excels in strategic thinking, long-term planning, and driving the maturity of data systems and practices. Your deep understanding of data infrastructure, business context, and modern data tooling will help position Guild's data engineering capabilities for future growth and innovation.

What You Bring

• 12+ years of data engineering or relevant experience, with demonstrated leadership in complex technical environments.
• Expert-level SQL skills, including advanced performance optimization, query tuning, complex CTEs, window functions, and data orchestration.
• Advanced proficiency in Python for sophisticated pipeline development, automation, API integrations, and scalable, maintainable code design.
• Data Trust is important to us, so significant experience implementing Change Data Capture (CDC) at scale is a must
• Extensive hands-on expertise with Databricks architecture and optimization, specifically around Unity Catalog, Medallion Architecture, MLFlow, and the Databricks MCP Platform
• Extensive hands-on expertise with Snowflake architecture and optimization, advanced dbt modeling strategies, and comprehensive integration using Fivetran.
• Strong command of infrastructure as code (Terraform), Unix/Linux environments, and version control (Git).
• Deep expertise in relational databases (Postgres, MySQL, AuroraDB) and substantial experience with NoSQL databases like DynamoDB.
• Advanced understanding of data modeling, warehousing methodologies, and modern ETL/ELT frameworks.
• Proven track record aligning technical designs to strategic business objectives and commercial outcomes.
• Experience leading technical initiatives within agile, high-growth environments utilizing modern data stack tools.
• In-depth knowledge of data governance, privacy, compliance standards, and regulatory frameworks.
• Expert understanding of CI/CD, continuous delivery, automated testing, and change management best practices.

Responsibilities

• Lead the architecture, design, and development of sophisticated, highly scalable data pipelines leveraging tools such as Fivetran, dbt, AWS Glue, Airflow, custom Python applications, Snowflake, Databricks, and cloud storage solutions (e.g., S3)
• Provide technical leadership in integrating and transforming complex data sets from diverse sources including AuroraDB, Snowflake, Postgres, MySQL, and DynamoDB.
• Drive collaboration with analytics, engineering, and commercial stakeholders to design and refine data models and marts that empower high-impact decision-making.
• Champion and implement rigorous data quality, validation, observability, and reliability standards across data workflows.
• Mentor and upskill team members, influencing the development of Guild’s data engineering practices and standards.
• Serve as a trusted advisor, guiding enterprise-wide data strategy, prototyping key data initiatives, and ensuring alignment of data engineering practices with long-term business and technical objectives.

We are committed to equal pay for equal work and believe in compensation