Want to lead the technical design behind modernizing AccuWeather For Business - the platform that delivers AccuWeather's data and services to more than half of the Fortune 500? We are looking for a Data Architect I who combines strong platform design expertise with the judgment to assess legacy infrastructure and design an implementable, cloud-native architecture; someone who wants to own the technical direction of a critical modernization initiative without compromising the reliability enterprise clients depend on. Reporting directly to the Data Architect II overseeing AccuWeather's data architecture function, this position will assess the legacy, on-premises infrastructure behind AccuWeather For Business and design the cloud-native architecture that will support its future. You will produce architecture and modernization design documents - including current-state assessments, target-state designs, transition and sequencing plans, and technical specifications - and work alongside engineering teams to implement key components of the architecture, while maintaining the reliability of the backend data systems that support critical data delivery services.
You will demonstrate high-level knowledge across cloud platforms and legacy enterprise systems, independently resolve complex architecture and modernization challenges, and collaborate closely with the Data Architect II and engineering teams. Your work will help modernize the technology foundation behind AccuWeather For Business, creating a more scalable, resilient, and cloud-native platform while maintaining the reliability expected by the Fortune 500 companies that depend on it.
We are open to hiring candidates to work from our global headquarters in State College, PA, USA, or remotely.
KEY RESPONSIBILITIES
• Assess the legacy, on-premises infrastructure behind AccuWeather For Business, documenting current-state architecture, system dependencies, data flows, and technical debt to inform modernization priorities.
• Design the cloud-native architecture, producing architecture designs, technical specifications, and other documentation needed to guide implementation.
• Own the architectural direction for the modernization effort, ensuring a cohesive approach across the platform rather than individual services or components.
• Develop a roadmap and sequencing plan that provides a practical path from the current environment to the cloud-native architecture while minimizing disruption to enterprise clients.
• Design backend data systems to maintain continuity of critical data delivery services throughout the transition.
• Partner with engineering and data teams to validate and implement architecture designs, ensuring solutions are secure, scalable, performant, and maintainable.
• Contribute hands-on to the implementation of architecture designs, including developing and modifying code, data models, schemas, and supporting data platform components.
• Estimate data consumption, capacity, and infrastructure requirements, incorporating cloud infrastructure costs into architecture decisions and trade-offs.
• Identify and document architectural and operational risks associated with modernizing a customer-facing production platform, and design appropriate mitigation strategies.
• Ensure the cloud-native architecture addresses performance, security, scalability, resiliency, recoverability, compliance, and data residency requirements.
• Understand system scheduling, integrations, and dependencies across the platform and incorporate them into planning and sequencing.
• Serve as a technical point of contact for questions and decisions related to the modernization effort's architectural direction.
QUALIFICATIONS
• Required Qualifications:
o BA/BS in Computer Science, Information Technology, or a related field, with 5+ years of experience in data or enterprise architecture, or MS with 3+ years of experience.
o High-level knowledge of cloud platforms (e.g., Microsoft Azure) and cloud-native architecture.
o Demonstrated experience assessing legacy, on-premises systems and designing modern, cloud-native architectures.
o Demonstrated experience planning or supporting large-scale modernization initiatives for production, customer-facing platforms.
o Experience designing production data platforms for performance, scalability, resiliency, and recoverability.
o Experience analyzing complex system dependencies, integrations, data flows, and scheduling requirements to inform architecture and modernization decisions.
o Demonstrated experience working with PostgreSQL, including relational data modeling, schema design, and query development.
o Advanced proficiency in Python or Go, with experience developing production-quality code for data platforms or backend systems.
• Preferred Qualifications:
o Experience designing backend data platforms that support data delivery to external or enterprise clients.
o Experience evaluating technology and architecture options, including build-versus-buy decisions and alternative modernization approaches.
o Experience evaluating infrastructure requirements and costs to inform cloud architecture decisions and design trade-offs.
o Familiarity with enterprise security, compliance, and data governance requirements, including SOC 2 and data residency considerations.
• Skills & Competencies:
o Strong systems thinking, with the ability to design architectures that engineering teams can implement and maintain effectively.
o Excellent written communication, with the ability to produce clear, actionable architecture and technical design documentation.
o Sound technical judgment, with the ability to translate business and platform requirements into pragmatic architecture without overengineering or underspecifying solutions.
o Ability to move effectively between architecture and hands-on implementation, translating designs into working solutions in collaboration with engineering teams.
o Ability to mentor team members and help develop the architectural judgment of less experienced engineers.
o Ability to independently lead complex, large-scale architecture initiatives and drive technical decisions through ambiguity.
