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Harvey is an AI platform transforming legal and professional services by combining frontier agentic AI with enterprise-grade infrastructure and deep domain expertise. The company is at a critical inflection point with strong product-market fit and world-class investor backing.
As one of the first hires on Harvey's central data platform team, you will architect and build the foundational systems enabling every team to work with data confidently and independently. This is a platform charter focused on leverage and trust across the organization, not a pipeline queue.
Your immediate focus will be establishing the ingestion and warehouse foundation: reliable streaming and batch paths into Snowflake, change data capture (CDC) from production systems, orchestration, and schema evolution that gracefully absorbs upstream changes. The platform must handle stringent data sensitivity requirements inherent to the legal services domain.
The charter expands to encompass transformation and compute frameworks, self-serve tooling for teams to build pipelines against well-tested primitives, real-time stream processing for products and internal systems requiring sub-batch latency, and quality/lineage/governance layers ensuring trustworthiness. Handling personally identifiable information (PII) correctly and honoring multi-region data residency are construction constraints, not afterthoughts, given Harvey's security-conscious customer base.
You will sit at the intersection of Analytics, Data Engineering, product teams, and Infrastructure, transforming today's distributed and improvised data work into a coherent system. You'll set technical direction, make deliberate build-versus-buy tradeoffs, and help build the team around you.
Key responsibilities include owning data platform architecture and technical direction; building and operating ingestion across streaming, batch, CDC, and third-party connectors; landing data into Snowflake with predictable freshness and cost; owning orchestration (scheduling, retries, backfills, dependency management); building transformation frameworks and self-serve tooling; designing stream processing infrastructure; implementing quality, observability, lineage, and cataloging layers; establishing PII and multi-region residency patterns; and setting technical standards through design reviews and mentorship.
About Harvey
Legal / Compliance / Risk; AI / Data / Infrastructure — AI platform for legal and professional services work.
