Senior Engineer, Platform & Data

LeanData•Santa Clara, CA

1d•$150,000 - $200,000•Onsite

About The Position

This role is based at our Santa Clara, CA office. You are required to be in office Mondays and Wednesdays each week. Lunch will be provided on those days. The Senior Engineer, Platform & Data will own and scale distributed ingestion and job systems, design and build the multi-tenant data platform, and ensure the reliability and observability of services. This role involves building for scale and concurrency, keeping the platform source-pluggable, and partnering directly with the SVP of Engineering on platform and data architecture.

Requirements

5+ years building production backend and distributed systems, with deep ownership of at least one of: high-throughput data pipelines, job or workflow systems, or multi-tenant data platforms
Strong, current Python (TypeScript a plus); you write and review production code
Distributed-systems fundamentals: concurrency, idempotency, consistency, partitioning, retries, and failure recovery; you have owned the correctness and uptime of data-intensive services in production
Strong cloud-native application development: containerized services, queues and workers, object storage, and relational data at scale (AWS or equivalent). This is a development role, not an infrastructure or SRE role: you build and operate your own services
Strong relational data modeling and SQL at scale (Postgres a plus); you've owned a production database schema and its evolution
High agency: you scope, prioritize, ship, and operate without waiting for permission

Nice To Haves

Worked against Salesforce or another large, messy enterprise data source (Bulk 2.0, REST, Pub/Sub, CDC)
Built multi-tenant isolation (Postgres + RLS), master-data management, entity resolution or survivorship, or watermark-based incremental sync
Experience with durable execution (Temporal, Inngest) and the modern eval/observability stack (Langfuse, Braintrust), though our stack is intentionally lean
A founder or founding-engineer background, or built a data platform 0-to-1

Responsibilities

Own and scale the distributed ingestion and job systems that pull customers' GTM data into the platform: full loads and incremental sync, correct and idempotent across many tenants and sources
Design and build the multi-tenant data platform the agents reason over and write back through: the canonical data model and its evolution, the serving and query layer, and the contracts other services depend on
Build for scale and concurrency from the start: many tenants, large enterprise orgs, hundreds of concurrent jobs and agent reads, with latency, cost, and correctness under failure as first-class concerns
Own the reliability and observability of your services: instrumentation, tracing, SLOs, and the operational health of the data plane
Keep the platform source-pluggable: extend ingestion to new systems behind a clean adapter contract without rewriting the engine
Partner directly with the SVP of Engineering on platform and data architecture, including schema evolution, survivorship, and entity resolution at scale, and set the patterns the team builds services on