高级软件工程师，数据平台
Senior Software Engineer, Data Platform
为什么选择Harvey
在Harvey，我们正在改变法律和专业服务的运作方式。通过结合前沿的代理AI、企业级平台和深厚的行业专业知识，我们正在重塑未来几十年关键知识工作的完成方式。
这是一个难得的机会，帮助打造一家具有时代意义的公司，在真正的转折点上共同前进。我们拥有强大的产品市场匹配度和世界级的投资支持。我们正在快速扩张，并实时定义一个新类别。工作充满雄心，标准很高，成长机会——个人、职业和财务上的——是无与伦比的。
我们的团队行动迅速，承担责任，并对使命充满热情——以高强度运作，贴近客户，不断追求卓越。我们秉持三个价值观：决断力、简洁性以及“工作未完成”。我们在清晰判断的基础上快速行动，而非等待完美信息；我们相信简洁才是可扩展的关键；我们从不满足于现状。如果你希望与志同道合的人一起完成职业生涯中最出色的工作，我们期待与你携手共创。
在Harvey，专业服务的未来正在今天被书写——而我们才刚刚开始。
职位概述
Harvey生成的数据远超我们目前能够有效利用的程度。产品遥测数据、代理执行追踪、模型使用情况、客户互动、财务和运营系统——数据量以及需要处理这些数据的团队数量都在快速增长，远远超过任何单一团队手动处理的能力。
作为我们核心数据平台团队的首批招聘人员之一，你将构建让Harvey所有团队都能自信且独立地使用数据的系统。这是一项平台职责，而非简单的流水线任务：你将构建框架、工具和已铺设好的路径，供产品工程师、数据工程师和分析师使用，你的价值由他们对我们的数据系统的依赖程度和普遍信任来衡量。
近期的基础是数据摄入和数据仓库——可靠的流式和批量路径进入Snowflake，从生产系统中进行变更数据捕获（CDC），编排以及能够吸收上游变化而非在压力下崩溃的模式演进，并考虑到我们领域所需的严格数据敏感性要求。
从这里，职责范围将扩展到现代数据平台应为用户提供的其他内容：转换和计算框架、自助工具，使团队可以基于经过验证的基本组件建立自己的数据管道、实时和
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WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
Harvey is generating far more data than we currently know how to use well. Product telemetry, agent execution traces, model usage, customer engagement, financial and operational systems — the volume and the number of teams who need to work with it are both growing faster than any single team can serve by hand.
As one of the first hires on our central data platform team, you'll build the systems that let every team at Harvey work with data confidently and independently. This is a platform charter, not a pipeline queue: you're building the frameworks, tooling, and paved paths that product engineers, data engineers, and analysts all build on, and you're measured by their leverage and general trust in our data systems.
The near-term foundation is ingestion and the warehouse — reliable streaming and batch paths into Snowflake, CDC off production systems, orchestration, and schema evolution that absorbs upstream change instead of breaking under it, and factors in the hard data sensitivity requirements our domain requires.
From there the charter expands to the rest of what a modern data platform owes its users: transformation and compute frameworks, self-serve tooling so teams can stand up their own pipelines against well-tested primitives, real-time and stream processing for products and internal systems that can't wait for a nightly batch, and the quality, lineage, and governance layers that make the whole thing trustworthy. Handling PII correctly and honoring multi-region data residency aren't nice to have features here — they're constraints the platform has to satisfy by construction, for customers who are among the most security-conscious institutions in the world.
You'll sit between Analytics, Data Engineering, product teams, and Infrastructure. Today this work is distributed and improvised. You'll make it a system, set the technical direction, and help build the team around you.
This role is based in San Francisco, CA or New York, NY
WHAT YOU'LL DO
- Own the data platform's architecture and technical direction — treating data infrastructure as a software product built from reusable frameworks, and making deliberate build-vs-buy tradeoffs as the platform grows
- Build and operate the ingestion layer across streaming, batch, CDC, and third-party connectors, including schema evolution that absorbs upstream change safely rather than silently breaking consumers, so onboarding a new source is a paved path instead of a project
- Land data into Snowflake with the freshness, completeness, and cost characteristics downstream consumers can plan around, and define a clean handoff for Analytics Engineering
- Own the orchestration platform — scheduling, retries, backfills, and dependency management across the full data graph
- Build the transformation and compute frameworks teams can use to process data at scale, and the self-serve tooling that lets product engineers and analysts stand up their own pipelines against primitives you've already made safe
- Design and operate stream processing infrastructure for use cases that can't wait for batch — real-time product features, operational alerting, and near-live reporting
- Build the trust layer: quality and observability (freshness, validation, reconciliation, anomaly detection, alerting routed to the right owner) alongside lineage, cataloging, and discovery, so anyone can find data and know where it came from and what depends on it
- Build the patterns and tooling for PII and sensitive data — classification, masking, retention, access control — and for multi-region residency requirements
- Set the technical bar for data at Harvey through design reviews, standards, documentation, and mentorship as the team grows
WHAT YOU HAVE
- 5+ years building and operating production data infrastructure, with ownership of systems other teams depend on
- Deep experience with cloud data warehouses — Snowflake strongly preferred (BigQuery, Databricks, or Redshift experience transfers well) — including performance tuning and cost management
- Hands-on experience building CDC and streaming pipelines with technologies like Kafka, Debezium, Flink, or Spark Streaming
- Experience with managed ingestion tooling (Fivetran, Airbyte, or similar) and clear judgment about when to buy the connector and when to build it
- Strong fluency with workflow orchestration — Temporal, Airflow, Dagster, or similar — operated at scale, not just configured
- Strong programming skills in Python and advanced SQL
- Experience building frameworks or internal tooling that other engineers use, and the product instinct to know when an abstraction is helping versus getting in the way
- Practical experience with data quality, observability, and lineage tooling, and with schema evolution in systems that can't afford downtime
- Working knowledge of data governance in a regulated environment: PII classification, masking, access control, retention, and data residency
- Familiarity with cloud data services (Azure, AWS, GCP), Kubernetes, and infrastructure-as-code (Terraform, Pulumi)
- Comfort operating in ambiguity and defining scope where none exists
NICE TO HAVE
- Experience with dbt and a close working relationship with analytics engineering teams
- Experience with lakehouse architectures and open table formats (Iceberg, Delta Lake) or query engines like Trino
- Experience operating multi-tenant platforms with strict security, compliance, or data residency requirements
- Exposure to data infrastructure for AI products
- Prior experience as an early or founding data platform hire at a fast-growing company
COMPENSATION
$193,400 - $290,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
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Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai