Live opening · Posted 6 days ago

Data Engineer

QuickLaunch Analytics · California, United States (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 6 days ago
CompanyQuickLaunch Analytics
LocationCalifornia, United States (Remote)
Salary$125K/yr - $155K/yr + Bonus, Profit sharing · 5 benefits
Work modeYes
SourceLinkedin
Listed6 days ago

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About the role

Description supplied by the original job listing.

Applicants without hands-on Databricks or Microsoft Fabric pipeline experience will not be considered.
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 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 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.
About Us:
At QuickLaunch Analytics, our purpose is to simplify the often-complex world of data analytics. For over 20 years, we’ve helped 250+ companies make better decisions by delivering a unified platform for trusted, enterprise-wide data.
We’re a team of 35+ professionals with deep expertise in Power BI, Databricks, and Azure Cloud. Our culture is built on ownership, collaboration, and continuous learning, reflected in strong outcomes for both our customers and our team.
If you enjoy solving complex data challenges and want to work closely with customers to deliver real-world impact, we’d love to hear from you.

Work arrangement
Yes

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