Senior Platform Data Engineer - Scale Multi-Tenant Pipelines

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

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.