About The Position

Guild is looking for a Senior Data & AI Platforms Engineer to join a small, high-performing team building the backbone of our data ecosystem. In this role, you will design, build, and scale the data infrastructure that powers analytics, operational insights, and product innovation across Guild. This is a high-impact, end-to-end ownership role for someone who brings a platform mindset and wants to shape how data drives decisions across the organization.

Requirements

  • Built and maintained production-grade data pipelines using tools like Snowflake, dbt, and Fivetran in a fast-paced, high-growth environment.
  • Designed scalable data models and warehousing solutions that connected technical infrastructure with commercial or product outcomes.
  • Worked cross-functionally with analytics, product, or business teams to translate data needs into reliable, self-serve solutions.
  • Navigated complex source systems (relational databases, NoSQL, APIs) and built integrations that handled messy, real-world data at scale.
  • Expert-level SQL (window functions, CTEs, performance tuning) and Python (data pipelines, API integrations, automation).
  • Hands-on experience with Snowflake, dbt, and Fivetran, plus comfort navigating Unix systems, Terraform, and Git.
  • Deep familiarity with relational databases (Postgres, MySQL, AuroraDB) and NoSQL systems such as DynamoDB.
  • Strong understanding of data modeling, warehousing best practices, and ETL/ELT frameworks.
  • Experience with CDC (Change Data Capture) patterns, data governance, or CI/CD practices in a data engineering context.
  • Proven ability to work cross-functionally and connect technical design with commercial objectives.

Responsibilities

  • Build and maintain reliable, scalable data pipelines that deliver trusted data to analysts, stakeholders, and product teams on time and without manual intervention.
  • Deliver accurate, well-modeled data marts and models that directly enable self-serve analytics and confident business decision-making.
  • Expand the data platform's scope to support production engineering use cases from the warehouse, establishing patterns and prototypes that the broader organization can adopt.
  • Architect, develop, and maintain data pipelines using Fivetran, dbt, S3, Glue, orchestrators, and custom Python jobs to keep data flowing reliably across the organization.
  • Manage and optimize data models in dbt, ensuring they are scalable, accurate, and aligned to business use cases.
  • Integrate and transform data from sources including AuroraDB, Snowflake, Postgres, MySQL, and DynamoDB.
  • Collaborate with analytics and commercial teams to design models and marts in visualization tools that empower decision-making.
  • Uphold data quality through testing, validation, and observability best practices.
  • Provide enterprise-wide guidance and prototyping on key data initiatives, especially as the platform expands to support production engineering from the warehouse.
  • Mentor and upskill team members while contributing to evolving data engineering standards and processes.

Benefits

  • Access to low-cost, high-quality health care options through Collective Health and Kaiser (due to coverage limitations, Kaiser is currently only available in CA & CO)
  • Access to a 401k to help save for the future
  • Vacation policy to rest and recharge
  • 8 days of fully-paid sick leave, to take the time to heal and or recover
  • Family-friendly benefits, including 12 weeks of parental leave for non-birthing parents and 18-20 weeks for birthing parents; 4-week ramp-up period for when employees return from a leave of 6 weeks or more; as well as employer-paid short-term and long-term disability, employer-sponsored life insurance, fertility and caregiving benefits.
  • Well-rounded wellness benefits including free and low cost mental health resources and financial wellbeing support services
  • Education benefits and tuition assistance to help your future development and growth
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