Senior Engineer, Platform & Data

leandata; United States; On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

Stock options

Flexible PTO

401K plan

Insurance premiums covered

Job summary

LeanData is seeking an experienced backend engineer to own and scale distributed ingestion and job systems for a multi-tenant data platform based in Santa Clara, CA. You will design the canonical data model, serving/query layer, and adapter contracts while ensuring latency, cost, and correctness across many tenants.

You will work closely with the SVP of Engineering on platform architecture, schema evolution, and survivorship at scale.

Qualifications

• 5+ years building production backend and distributed systems with ownership of data pipelines or multi-tenant platforms.
• Strong Python skills; TypeScript a plus; production code experience.
• Fundamentals of concurrency, idempotency, consistency, partitioning, retries and failure recovery.
• Cloud-native development with containers, queues/workers, object storage, and relational data at scale.
• Strong SQL skills including PostgreSQL and production database schema evolution.

Responsibilities

• Own and scale ingestion and job systems pulling customer GTM data into the platform.
• Design and build the multi-tenant data platform and its serving/query layer.
• Build for scale with many tenants, large enterprises, and high concurrency.
• Own reliability and observability: instrumentation, tracing, SLOs, and health of the data plane.
• Keep platform source-pluggable with adapters and clean contracts.
• Collaborate with SVP of Engineering on platform architecture and data patterns.

Skills

Python

TypeScript

SQL

PostgreSQL

Distributed systems

Cloud-native

Concurrency

Tools

AWS

Docker

Kubernetes

Job description

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.

What you'll be doing:

• 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

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

Bonus points if you have:

• 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

Compensation:

The salary for this role will be between $150k and $200k. We typically refrain from offering at the upper limit of the salary range to allow for future development within the role, ensuring that compensation can be adjusted to reflect an individual's advancing skills and contributions to the team while maintaining internal fairness.

Why work at LeanData:

• LeanData covers employee insurance premiums up to 90%
• Stock options in LeanData for all full-time employees
• Flexible PTO
• 401K plan