Data Platform Engineer

QuickLaunch Analytics•Santa Cruz, CA

1d•$125,000 - $155,000•Hybrid

About The Position

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.

Requirements

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 tools like 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 Haves

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

Responsibilities

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