Solutions Architect - Digital Native Business (Geo)

Role overview Lead technical strategy for customer accounts adopting a cloud data and AI platform, from early discovery through production deployment and ongoing usage growth. You will advise senior technical stakeholders, design scalable architectures across data engineering, machine learning, and real-time analytics, and build recognized depth in a technical specialization.

Responsibilities - Own account-level technical strategy, translating customer needs into architecture and adoption plans. - Lead design discussions and reviews for production-grade data pipelines, streaming systems, analytics, and AI solutions. - Advise customer architects, engineering leads, and directors; explain design choices and trade-offs clearly. - Build tailored demonstrations and solutions to establish technical value in competitive evaluations. - Coordinate specialists and partners to address complex customer requirements. - Share structured customer and market feedback with product teams, and support increased platform adoption and usage.

Requirements - At least six years in solutions architecture, data engineering, technical presales, or a senior hands-on technical role. - Strong Python and SQL skills, including the ability to code, debug, and build solutions live. - Deep understanding of distributed data systems, scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native platforms. - Experience deploying production workloads on AWS, Azure, or Google Cloud, including infrastructure, security, and governance considerations. - Ability to lead architecture conversations with senior stakeholders and communicate technical choices in terms of business value. - Bachelor’s or master’s degree in computer science, engineering, or a quantitative field, or equivalent experience.

Nice to have - Developing specialization in areas such as streaming, machine learning and AI, data governance, or migrations. - Relevant platform certifications, familiarity with competing data platforms, or experience at a data/AI company or cloud provider. - Industry expertise in fields such as finance, healthcare, retail, or media.