Staff Analytics Engineer

Intrado is dedicated to saving lives and protecting communities, helping them prepare for, respond to, and recover from critical events. The Staff Analytics Engineer will transform raw data into trusted business insights and partner with the Staff Data Engineer to architect the end-to-end delivery of the data ecosystem, ensuring timely and actionable insights for leadership.

Responsibilities:

• End-to-End Data Architecture: You will partner with the Staff Data Engineer to architect the complete data lifecycle. While they build the infrastructure, you will own the gold layer, designing the semantic layer and transforming silver level data in Databricks into optimized fact and dimension tables that serve as the single source of truth for the company
• Business Logic & Strategy: Translate complex, ambiguous business questions into concrete technical definitions. You will act as the key technical liaison to build consensus on enterprise-wide metric definitions, ensuring consistent logic across all reports
• Data as a Product: Champion a product-oriented mindset by setting the standard for robust documentation, testing, and data model design
• Mentorship & Standards: You will lead by example on best practices and code quality to ensure engineering rigor
• Performance Tuning: Optimize the connection between Databricks and Power BI, designing models that balance computational load with query latency to ensure dashboards perform

Requirements:

• 10+ years of relevant, progressive experience in Analytics Engineering, Software Engineering, or Data Engineering, with at least 4 years working in large-scale data lake/warehouse environments (e.g., Databricks). Prior ownership of large-scale data systems and business-critical metrics
• Mastery of dimensional modeling best practices. You must be an expert in designing modular, reusable, and performant data models (Star Schema, Snowflake Schema) that serve as the foundation for analytics
• Proficiency in advanced SQL techniques and performance tuning
• Experience leveraging LLMs and AI-assisted development tools to accelerate data engineering workflows, improve code quality, and automate repetitive technical tasks
• Strong expertise in Python for scripting, automation, and data manipulation (Pandas)
• Deep proficiency in Power BI or Tableau, understanding how to architect semantic models that enable polished, high-performance dashboards for executive stakeholders
• Strong ability to translate technical concepts into business value. You must be able to partner with non-technical stakeholders to define gold level metrics and manage projects across teams
• Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a closely related technical field
• Master's or equivalent in Computer Science, Data Science, Analytics or Engineering
• Prior experience working in a technology company or SaaS environment