Enterprise Data Strategist
Edisyl, identified in the site’s patent disclosure as Flipside Crypto Inc, provides enterprise semantic-data infrastructure and AI-agent systems. It helps organizations encode internal metric definitions and connect data sources so AI systems, pipelines, and intelligence workflows can operate using the organization’s own business context.
Funding history
About edisyl
Edisyl builds a semantic layer for enterprise data that captures organizational definitions, metric logic, and otherwise undocumented knowledge, then binds that context to existing data systems. Its platform comprises Stratum, the semantic intelligence layer; Forge, an agent framework and tools layer; and Lattice, agent-fleet orchestration. The company deploys these capabilities in client environments for use cases including lead scoring, CRM write-back, automated briefings, multi-source data connectivity, and generation and validation of DBT transformation pipelines. Its foundation includes prior blockchain-data infrastructure and entity-resolution work across multiple chains.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will assess enterprise data environments, define target architectures, and develop phased AI-activation roadmaps. You will lead executive workshops, establish governance and readiness frameworks, translate strategy into implementation plans, identify expansion opportunities, and codify the delivery methodology.
Requirements
- 6–10 years of data strategy and client or executive advisory experience
- Experience running executive-facing workshops
- Experience translating business needs into data requirements
- Knowledge of data mesh, lakehouse architecture, batch and real-time processing, and governance frameworks
- Experience in financial services, insurance, or crypto/blockchain infrastructure preferred
Responsibilities
- Lead enterprise data strategy engagements
- Assess current data environments and define target architectures
- Develop phased roadmaps toward AI activation
- Run executive workshops on business, data, and AI priorities
- Define data governance, quality, and readiness frameworks
- Translate strategic intent into implementation plans with Forward-Deployed Engineers
- Identify expansion opportunities and AI use cases
- Codify methodology and contribute to market positioning
Benefits
- Meaningful early-stage equity
- Variable compensation tied to engagements and expansions
- Remote work
