Staff Data Engineer (Scottsdale)

What You'll Do: Define and evolve enterprise-wide data architecture, engineering standards, and technical best practices. Design and build scalable, resilient, and cost-efficient data platforms using AWS and modern data technologies. Lead complex, cross-functional data initiatives spanning multiple teams, systems, and business domains. Develop and optimize data solutions using Python, SQL, Apache Spark, and cloud-based data technologies. Evaluate architectural tradeoffs between AWS-managed services and open-source technologies such as Spark, Flink, and Iceberg. Establish standards for data quality, governance, security, observability, and reliability. Drive alignment around data modeling, batch and real-time data integration, and platform usage. Serve as a technical authority for complex engineering challenges, architecture decisions, and production issues. Mentor senior engineers through technical guidance, architecture discussions, and design reviews. Apply AI and GenAI capabilities in production to improve engineering workflows, automation, operational efficiency, and developer productivity. Identify technical debt and continuously improve the scalability, performance, and maintainability of data platforms. Partner with engineering, analytics, and business leaders to translate strategic objectives into effective technical solutions.

What We're Looking For: Bachelor's degree in Computer Science, Information Systems, Computer Engineering, or a related field; equivalent experience will also be considered.8+ years of experience in data engineering, software engineering, or platform engineering. Strong hands-on programming experience with Python, SQL, and Apache Spark. Extensive experience designing and implementing cloud-based data platforms using AWS.Strong understanding of data architecture, data engineering, data governance, and cloud architecture. Experience building and maintaining large-scale, mission-critical production data systems. Expertise in data modeling, data warehousing, distributed systems, and performance optimization. Experience with infrastructure as code (IaC), CI/CD pipelines, and engineering automation. Strong knowledge of data quality, observability, security, reliability, and compliance practices. Experience leading cross-team technical initiatives and influencing architectural decisions. Demonstrated ability to mentor engineers and provide technical leadership without requiring direct people-management responsibility. Experience applying AI or GenAI in production engineering environments to improve automation, workflows, or developer productivity. Strong problem-solving, debugging, and root-cause analysis skills. Why Consider This Opportunity? Take ownership of enterprise-level data architecture and technical direction. Work with modern cloud technologies and large-scale data systems. Influence engineering standards and best practices across multiple teams. Combine hands-on development with technical leadership and mentorship. Help drive the adoption of AI-enabled engineering practices. Interested in taking the next step in your data engineering career? Apply today!