Solutions Architect
RemoteUnited States or India
Job Summary
Lead discovery sessions to uncover business goals and translate complex client challenges into scalable, production-ready Data & AI architectures. Serve as the primary technical advisor throughout engagements, providing clear recommendations on tooling, implementation approaches, and technical trade-offs while developing architecture diagrams and design documentation. Lead and own the successful delivery of enterprise solutions from discovery through production deployment, guiding engineering teams through implementation and proactively removing delivery blockers. Leverage AI throughout the software delivery lifecycle to improve solution design, engineering productivity, and client outcomes. Mentor engineers through architectural guidance, design reviews, and technical coaching while contributing to hiring and onboarding. Partner with clients and executive stakeholders to navigate complex architectural decisions and deliver measurable business value.
Required Qualifications
- 8+ years of experience in Solutions Architecture, Data Engineering, or related consulting roles
- Proven experience designing and delivering enterprise Data & AI solutions into production within cloud environments
- Demonstrated experience delivering with AI, leveraging modern AI technologies throughout the software delivery lifecycle to improve solution design, engineering productivity, code quality, testing, documentation, troubleshooting, and client outcomes
- Strong consulting experience leading technical discovery, solution architecture, and client-facing engagements
- Hands-on experience with many of the following cloud and data platforms: Snowflake, Databricks, Google BigQuery, AWS, Microsoft Azure, Google Cloud Platform
- Hands-on experience with data engineering technologies: Python, SQL, Java and/or Scala, Spark, Kafka, Airflow, dbt, Fivetran, Matillion, or similar technologies
- Experience with modern engineering practices including: CI/CD, Infrastructure as Code, observability, and monitoring
- Experience incorporating AI into day-to-day engineering and solution delivery using technologies such as: Anthropic Claude, OpenAI, GitHub Copilot, Microsoft Copilot, Google Gemini, Snowflake Cortex AI, AWS Bedrock, LangChain, LangGraph, or similar enterprise AI development platforms and frameworks
Desired Qualifications
- Industry certifications across Snowflake, AWS, Azure, GCP, Anthropic, and/or Databricks
- Contributions to technical communities through speaking, writing, open source, or internal enablement
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