Staff Software Engineer, Data Platform

At Harvey were transforming how legal and professional services operate. By combining frontier agentic AI an enterprise-grade platform and deep domain expertise were 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. Were 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 Jobs Not Finished. We act quickly on clear judgment over perfect information we believe simplicity is what scales and were never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive wed love to build with you.

At Harvey the future of professional services is being written today and were just getting started.

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 youll build the systems that let every team at Harvey work with data confidently and independently. This is a platform charter not a pipeline queue: youre building the frameworks tooling and paved paths that product engineers data engineers and analysts all build on and youre 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 cant 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 arent nice to have features here theyre constraints the platform has to satisfy by construction for customers who are among the most security-conscious institutions in the world.

Youll sit between Analytics Data Engineering product teams and Infrastructure. Today this work is distributed and improvised. Youll 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

• Own the data platforms 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 youve already made safe

• Design and operate stream processing infrastructure for use cases that cant 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

• 10 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 cant 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

• 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

$231000 - $340000 USD

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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

Required Experience:

Staff IC