Data Product Architect

Responsibilities

• Lead the architecture, design, and evolution of enterprise data products and platforms aligned with business priorities and technology strategy.
• Partner closely with business stakeholders to understand challenges, identify opportunities, and translate requirements into scalable technical solutions.
• Design and implement cloud-native data architectures leveraging AWS services and modern data engineering practices.
• Provide technical leadership across the software development lifecycle, guiding engineering teams on architecture, design patterns, and solution implementation.
• Collaborate with architects, product teams, and technology partners to ensure alignment with enterprise architecture standards and roadmaps.
• Develop and optimize data pipelines, data integration solutions, and data platforms that support analytics and operational use cases.
• Evaluate technologies, tools, and vendor solutions to support future product capabilities.
• Support architecture governance processes and contribute to technology standards and best practices.
• Mentor engineers and foster technical excellence across the team.
• Drive delivery outcomes by balancing business needs, technical feasibility, scalability, and long-term sustainability.

• Minimum of five years related work experience, with at least two years of development experience.
• Undergraduate degree or equivalent combination of training and experience.
• Experience architecting and building cloud-based data platforms using AWS.
• Strong programming and data engineering experience with Python, SQL, and PySpark.
• Experience designing and supporting large-scale data pipelines and distributed data processing solutions.
• Knowledge of modern data architecture patterns, data modeling, and enterprise data ecosystems.
• Experience partnering with business stakeholders and translating business requirements into technical solutions.
• Strong communication, collaboration, and stakeholder management skills.

• Experience with data visualization and analytics platforms such as Tableau, Power BI, or Amazon QuickSight.
• Experience providing technical leadership, mentorship, and architectural guidance to engineering teams.