DBT Architect

We are seeking a DBT Architect to lead the design and evolution of our high-performance data infrastructure. In this role, you will be responsible for creating resilient, vendor-agnostic data environments that support diverse organizational needs. We value architectural clarity, technical rigor, and a commitment to building sustainable data ecosystems. Our team thrives on collaboration and continuous learning, and we welcome applicants from all backgrounds.

As a DBT Architect, you will lead decisions on compute engines, tiered storage, and open-table formats. You will ensure our platform remains interoperable and secure, defining standards for data pipelines and automated governance. Your role involves documenting technical trade-offs through Architectural Decision Records and balancing performance optimization with cost-efficiency.

SQL,Pyspark,Python,Data Bricks,Snowflake,Snowflake / Redshift,DuckDB,Data Build Tool (Dbt)

Extensive experience in Data Engineering and Architecture, specifically delivering production-grade Lakehouse environments.

• Proficiency with the Modern Data Stack, including Databricks (Unity Catalog), Amazon Redshift, or Snowflake.
• Hands-on expertise with Open-Table Formats such as Apache Iceberg or Delta Lake, including optimization and schema evolution.
• Advanced SQL-based modeling skills using dbt (Core) and data processing experience with PySpark or Python.
• Experience with orchestration tools like Apache Airflow, focusing on dependency-aware DAGs.
• Knowledge of cloud ecosystems (AWS, Azure, or GCP) with an emphasis on storage-compute separation.
• Understanding of Kubernetes (K8s) including Pods, Services, and Secrets management.
• Ability to communicate complex technical roadmaps and debt to senior leadership and stakeholders.
  
  

Preferred Skills And Experience

• Familiarity with vectorized or embedded engines like DuckDB for specialized processing.
• Experience with open-source catalog implementations like Apache Polaris.
• Knowledge of Data Ops principles and automated testing frameworks.
• Experience managing both fixed-resource infrastructure and elastic serverless models.
• Understanding of PII discovery and row/column-level security implementations.