Senior Databricks Platform Engineer - Data Pipelines & AI

BC Forward; Seattle (WA); Hybrid; USD 83,000 - 90,000; Part time

Job summary

BCforward is seeking a Senior Databricks Platform Engineer to join our team. The role focuses on Databricks platform engineering, data pipeline development, CI/CD, IaC, and data governance to deliver reliable data platforms and accelerate research-to-production workflows.

The candidate will design and implement platform capabilities, build reusable data products, and improve data quality, observability, and monitoring in a fast-paced consulting environment.

Qualifications

• 8+ years of platform and data solutions experience.
• Hands-on Databricks experience across workspace, notebooks, and jobs, with a focus on platform capabilities.
• Proficiency in Python.
• Proficiency in SQL.
• Modern CI/CD and Infrastructure as Code, with Terraform strongly preferred.
• Data governance and observability, including Unity Catalog, lineage, and monitoring.
• Orchestration with Airflow.
• AI fluency, including use of AI agents to design, build, test, and support solutions.

Responsibilities

• Design, build, and enhance platform capabilities within Databricks and related technologies.
• Build reusable data products and self-service capabilities.
• Design and maintain data pipelines and integration frameworks.
• Improve data quality, reliability, lineage, and monitoring.
• Accelerate research-to-production delivery by prototyping with researchers, establishing production patterns, and reducing friction between research and engineering workflows.

Skills

Databricks platform engineering

Python

SQL

CI/CD

Airflow

Unity Catalog

Observability

Data governance

Tools

Terraform

Airflow

Job description

BCforward is seeking a Senior Databricks Platform Engineer to join our team. The role focuses on Databricks platform engineering, data pipeline development, CI/CD, IaC, and data governance to deliver reliable data platforms and accelerate research-to-production workflows.

The candidate will design and implement platform capabilities, build reusable data products, and improve data quality, observability, and monitoring in a fast-paced consulting environment.