Staff Data Engineer
SKYTOUCH Solutions
** This role is not eligible for sponsorship AND is four days onsite hybrid at our N. Scottsdale office ** Who are we looking for? Choice Hotels has an exciting new opportunity as a Staff Data Engineer in the SkyTouch Technology division . SkyTouch Technology, is an independently operated division of Choice Hotels that provides the most widely used cloud-based (SaaS) hotel property management system. As a key member of our SkyTouch Software Engineering - Data, you will drive enterprise-wide impact by shaping scalable, reliable data architectures and standards that enable teams to deliver trusted data, accelerate innovation, and support long-term business strategy. Are you a systems-level data engineer who thinks beyond individual pipelines to shape enterprise-wide data architecture and standards? Do you thrive on influencing technical direction and enabling multiple teams to succeed at scale? The #SkysTheLimit when you #MakeItYourChoice ! We encourage you to apply today! Your Responsibilities
- Define and evolve the long-term data architecture and technical standards across teams and platforms
- Design and oversee highly scalable, resilient, and cost-efficient data systems using cloud technologies (e.g., AWS)
- Make principled tradeoffs between AWS-managed services and open technologies (e.g., Spark, Flink, Iceberg) to ensure long-term scalability and maintainability.
- Lead complex, cross-domain data initiatives that span multiple teams, systems, and business functions
- Serve as a technical authority and escalation point for complex data engineering challenges and architectural decisions
- Establish best practices for data quality, reliability, observability, security, and governance across the organization
- Drive alignment on data modeling, batch and real-time integration patterns, and platform usage to reduce duplication and technical debt
- Partner with engineering, analytics, and business leaders to translate strategic goals into technical data solutions
- Mentor senior engineers and influence technical growth through design reviews, architecture forums, and technical guidance
- Use an AI-first approach to mitigate systemic risks, improve engineering productivity focusing on automation and operational efficiency
- Balance near-term delivery with long-term platform health, scalability, and sustainability
- Bachelor's degree in related field Computer Science, Information Systems, Computer Engineering or equivalent experience
- Minimum of 8+ years of experience in data engineering, software engineering, or platform engineering roles.
- Proven experience designing and evolving large-scale, cloud-based data platforms in AWS.
- Experience leading cross-team, multi-system data initiatives with long-term architectural impact
- Demonstrated ownership of mission-critical production data systems
- Experience influencing technical direction across teams without direct people management
- Expert-level knowledge of cloud data architectures and AWS data services
- Advanced data modeling and data warehousing design expertise.
- Acts as a trusted technical authority, guiding architectural decisions, mentoring senior engineers, and influencing outcomes across teams.
- Strong programming skills (Python, SQL, and/or Spark)
- Deep understanding of distributed systems, performance tuning, and scalability
- Infrastructure-as-code, CI/CD, and automation expertise.
- Ability to design scalable, fault-tolerant, and cost-efficient data architectures
- Strong understanding of distributed systems, data partitioning, and performance tuning
- Expertise in data quality, observability, and reliability practices
- Knowledge of data governance, security, and compliance best practices
- Strong debugging and root-cause analysis skills across data pipelines and cloud infrastructure.
- Designing for reliability, observability, fault tolerance, and cost efficiency at scale
- Implementing organization-wide standards for data quality, security, and governance
- Identifying and reducing technical debt across data platforms
- Experience applying AI/GenAI in production to engineering workflows, automation, data quality, or developer productivity
- Demonstrates key competencies to include managing complexity, valuing differences, and cultivating innovation
Vacancy posted 1 day ago
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