Solutions Architect - CPG and Manufacturing
Own customer-facing technical strategy for data and AI platform adoption, designing production-grade architectures and leading complex solution discussions. The role requires 6+ years of relevant experience, cloud deployment expertise, and strong communication with technical and executive stakeholders.
About the job
Responsibilities
- Own end-to-end technical strategy for customer accounts, from discovery through production deployment.
- Drive competitive wins by building differentiated AI and data solutions that accelerate platform consumption.
- Lead architecture discussions and design production-grade solutions across data engineering, AI/ML, agentic systems, and real-time analytics.
- Partner with customer architects, engineering leads, and directors on their data and AI journeys.
- Develop a technical specialization in areas such as AI/ML, agentic systems, real-time streaming, data governance, or migrations.
- Coordinate DSAs, SSAs, and partners to deliver end-to-end solutions.
- Provide structured customer and competitive feedback to product teams.
Requirements
- 6+ years of experience in solutions architecture, data engineering, data science/AI, or technical pre-sales.
- Strong record of hands-on solution building and customer-facing technical leadership.
- Deep expertise in modern data and AI architectures, including lakehouse design, scalable pipelines, real-time/streaming systems, and cloud-native platforms.
- Understanding of AI/ML concepts, agentic architectures, and ontology design, including compound AI systems, autonomous agent frameworks, knowledge graphs, and semantic data models.
- Proficiency with the Databricks Platform or ability to become proficient rapidly.
- Experience with production deployments on AWS, Azure, or Google Cloud, including security and governance considerations.
- Track record of driving platform adoption and consumption growth for AI/ML and data analytics workloads.
- Excellent communication skills for translating complex architectures into business value.
- Bachelor's or master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.
Nice to Have
- Databricks certifications in data engineering, machine learning, or platform technologies.
- Experience with Snowflake, AWS native services, or Azure Synapse.
- Background at an AI-first company, data platform vendor, or cloud provider.
- Industry expertise in CPG and Manufacturing, Financial Services, Healthcare, Retail, or Media.
Skills
Solutions Architecture, Databricks, Data Engineering, Data Science, AI/ML, Lakehouse, Real-Time Analytics, Streaming, AWS, Microsoft Azure, GCP, Agentic Architectures, Knowledge Graphs, Semantic Data Models, Snowflake
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