Databricks Platform Engineer: Build Data Products to Production

Glint Tech Solutions; Irvine (CA); Hybrid; USD 165,000 - 248,000; Part time

Job summary

Glint Tech Solutions is seeking a Data Platform Engineer to design and build scalable data infrastructure using Databricks for enterprise clients. The role focuses on creating reusable data products, data pipelines, and robust production-ready capabilities while emphasizing governance and observability.

You will collaborate with researchers and engineers to accelerate prototypes into production, leveraging modern data tooling and AI-assisted approaches to deliver reliable data services.

Qualifications

• 8+ years of platform and data solutions experience.
• Hands-on Databricks experience (workspace, notebooks, jobs) and platform capability development.
• Proficiency in Python and SQL.
• Experience with CI/CD and Infrastructure-as-Code (Terraform strongly preferred).
• Knowledge of data governance, lineage, monitoring and observability.
• Experience with orchestration (Airflow).
• Hands-on use of AI agents (Claude Code) 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.
• Partner with researchers to prototype solutions and establish production delivery patterns.

Skills

8+ years of experience

Databricks experience

Python

SQL

Terraform / IaC

Data governance & observability

Airflow

AI fluency with agents

Tools

Databricks (workspace)

Job description

Glint Tech Solutions is seeking a Data Platform Engineer to design and build scalable data infrastructure using Databricks for enterprise clients. The role focuses on creating reusable data products, data pipelines, and robust production-ready capabilities while emphasizing governance and observability.

You will collaborate with researchers and engineers to accelerate prototypes into production, leveraging modern data tooling and AI-assisted approaches to deliver reliable data services.