Data Platform Engineer

Integratedcooling; Santa Cruz (CA); Hybrid; USD 125,000 - 155,000; Full time

Job summary

Integratedcooling is seeking a Data Platform Engineer to design and deliver modern data platforms while collaborating with customers. You'll work with Azure, Databricks, and Microsoft Fabric for implementing scalable, production-ready data solutions in a hybrid environment.

The ideal candidate has strong hands-on experience with Databricks, Python, and SQL, along with a solid foundation in data modeling and ETL tools. This role offers a competitive salary range of $125,000 to $155,000 with bonus opportunities.

Qualifications

• Strong hands-on experience with Databricks and/or Fabric.
• Solid foundation in database concepts and data modeling.
• Experience with ETL/ELT tools and data integration.

Responsibilities

• Design and deploy modern data platforms in Azure Databricks.
• Build scalable data pipelines using Python and SQL.
• Lead customer implementations and technical delivery.

Skills

Databricks

Python

SQL

ETL/ELT tools

Data modeling

Job description

Overview

At QuickLaunch Analytics, we help organizations simplify the complex world of data. As a Data Platform Engineer, you will play a critical role in designing, building, and delivering modern data platforms for our customers while also partnering directly with them to ensure successful deployment and adoption.

This is a highly impactful, hybrid role that blends hands‑on engineering with customer‑facing consulting. You’ll work across Azure, Databricks, and Microsoft Fabric to implement scalable, production‑ready data solutions that power enterprise analytics.

What You’ll Do

• Design and deploy modern data platforms in Azure Databricks, including full environment setup (storage, compute, catalogs, security) and infrastructure optimization
• Build scalable data pipelines and Lakehouse solutions using Python, SQL, and orchestration across Databricks and Microsoft Fabric
• Lead customer implementations and technical delivery, supporting new deployments, upgrades, and escalation troubleshooting in Azure environments
• Develop and manage ETL/ELT integrations across third‑party tools and custom APIs, ensuring reliable, production‑grade data workflows
• Implement secure, high‑performance data architectures, including Unity Catalog, OneLake security, networking (VPNs, private endpoints), and cost optimization
• Partner directly with customers as a technical advisor, translating business needs into data platform solutions and driving best practices across Databricks and Fabric

Who You Are

• Strong hands‑on experience with Databricks and/or Fabric, Spark, Python, and SQL, with the ability to build and troubleshoot production‑grade data pipelines
• Solid foundation in database concepts and data modeling, with experience working across structured and semi‑structured datasets
• Experience with ETL/ELT tools and data integration, including Fivetran and building/customizing API‑based data pipelines
• Comfortable working in customer‑facing or consulting environments, supporting new implementations in Azure Databricks or Microsoft Fabric
• Working knowledge of identity and access management concepts (e.g., Entra ID users, groups, and permissions)
• Strong aptitude for diagnosing, isolating, and resolving complex technical issues efficiently
• Ability to communicate effectively with both technical and non‑technical customers and team members

Nice to Have

• Experience using AI and automation tools to streamline workflows, including exposure to AI agents or intelligent automation frameworks
• Experience configuring private endpoints in Azure, including networking setup and DNS configuration
• Understanding of Power BI and Fabric licensing and how licensing might impact deployment approach
• Familiarity with Linux environments and cloud‑based data ecosystems

Working Location: Remote (USA) or hybrid (Santa Cruz County, CA)

Compensation: The estimated base salary range for this role is $125,000-155,000. There is also an opportunity for a discretionary bonus.