Solutions Architect
Role details
Job location
Tech stack
Job description
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Lead the end-to-end architecture and solutioning of a greenfield enterprise data platform serving as a single source of truth
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Partner with business and technical stakeholders to translate ambiguous requirements into scalable, secure, cloud-based data solutions
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Design and guide implementation of modern analytics architectures, including data lakes and lakehouse patterns (bronze/silver/gold)
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Evaluate and help select the core data platform (e.g., Snowflake or Databricks) and supporting cloud services
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Architect data ingestion and integration from multiple heterogeneous source systems (e.g., 15+ databases with varying architectures)
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Ensure strong foundations in data governance, master data management (MDM), data quality, and security
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Build and/or guide POCs to demonstrate business value and ROI
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Act as a trusted advisor, communicating architectural decisions clearly to audiences ranging from engineers to VPs and CFOs
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Collaborate with engineering, analytics, and business teams in a consultative solution architecture role
What Success Looks Like
- Establishes a scalable, governed data foundation that enables reliable analytics and future AI use cases
Requirements
Required Qualifications (Must Haves)
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Hands-on experience with Snowflake or Databricks (or a comparable modern cloud data platform)
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Proven background in cloud-based data architecture (AWS preferred; Azure experience a plus)
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Strong foundation in data engineering and analytics solutioning, not just infrastructure
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Experience designing enterprise-scale data platforms, including ingestion, transformation, and reporting layers
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Deep understanding of data governance, MDM, and how these influence platform architecture and design
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Ability to explain and implement bronze/silver/gold data patterns and articulate their business value
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Excellent communication and stakeholder management skills, with the ability to operate effectively from technical teams through executive leadership * Experience working in highly regulated environments
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Exposure to AI/ML enablement through modern data platforms
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Background in enterprise architecture or data product architecture