Enterprise Data Strategist

Edisyl•Boston, MA

20h•Remote

About The Position

This role is for an Enterprise Data Strategist who can identify and solve complex data challenges for enterprise customers. The ideal candidate will have strong diagnostic skills to uncover the root cause of data-related issues, rather than just addressing stated symptoms. This individual will be responsible for scoping engagements, leading strategy discussions, and ensuring successful delivery of AI solutions. The role involves significant autonomy, shaping methodology, and influencing go-to-market strategies for major clients. The company, edisyl, builds AI solutions using institutional data, with a background in blockchain data infrastructure and active deployments with major clients.

Requirements

6–10 years of experience combining data strategy with direct client or executive advisory exposure (e.g., senior engagement manager or principal-level at a data or management consulting firm, or director-or-above in a large enterprise data organization).
Experience running executive-facing workshops and translating ambiguous business needs into structured data requirements.
Strong grasp of modern data architecture: data mesh, lakehouse, real-time vs. batch, governance frameworks.
Experience in at least one priority vertical: financial services, insurance, or crypto/blockchain infrastructure (strongly preferred).
Sharp diagnostic instincts to quickly identify the real problem in new environments.
Comfort with ambiguity in enterprise data environments and conversations.
Outcome orientation: measuring success by client business changes, not just on-time delivery.
Strong opinions on enterprise AI requirements versus vendor promises.

Nice To Haves

Background at a firm known for forward-deployed or consultative advisory (e.g., McKinsey Data, Palantir, Databricks professional services, or similar).
Experience working directly with a CEO or founder in a small-company or build-out context.
Familiarity with blockchain data, DeFi, or institutional crypto infrastructure.

Responsibilities

Lead data strategy engagements with enterprise customers, assessing current state, defining target architecture, and developing phased roadmaps for AI activation.
Run executive-level workshops to align business objectives with data and AI investment priorities.
Define data governance, quality, and readiness frameworks to accelerate customer value realization.
Partner with Forward-Deployed Engineers to translate strategic intent into executable implementation plans.
Identify expansion opportunities by connecting latent data assets to new AI use cases.
Codify methodology and contribute to edisyl's market positioning through thought leadership.