Data Engineer

QuickLaunch Analytics helps organizations simplify the complex world of data and deliver trusted enterprise-wide analytics platforms. The company is seeking a Data Platform Engineer to design, build, and deploy modern data solutions across Azure, Databricks, and Microsoft Fabric while also partnering with customers on implementation, troubleshooting, and adoption.

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

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
• • 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