Senior Engineer, Platform & Data

LeanData; Santa Clara (CA); On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

Stock options

Flexible PTO

401K plan

Insurance premium coverage (90%)

Job summary

LeanData in Santa Clara, CA, is seeking a backend engineer to own and scale distributed data ingestion and job systems for multi-tenant customers.

You will design the canonical data model, ensure high concurrency, and build reliable, observable services running on cloud-native infrastructure. Strong Python and SQL skills are essential, with experience in Postgres a plus.

Qualifications

• 5+ years building production backend and distributed systems with ownership of data pipelines or multi-tenant platforms.
• Strong Python and/or TypeScript; write and review production code.
• Fundamentals of distributed systems: concurrency, idempotency, consistency, partitioning, retries, failure recovery.
• Cloud-native app development: containers, queues, storage, relational data at scale; build and operate your services.
• Strong relational data modeling and SQL at scale; production schema evolution.
• High agency: scope, prioritize, ship, and operate without waiting for permission.

Responsibilities

• Own and scale the distributed ingestion and job systems for multi-tenant data.
• Design and build the multi-tenant data platform and canonical data model.
• Scale for many tenants with high concurrency, latency and cost considerations.
• Own reliability and observability: instrumentation, SLOs, and health of the data plane.
• Keep the platform source-pluggable with adapters for new systems.
• Collaborate with SVP of Engineering on data architecture and patterns.

Skills

Backend engineering

Python/TypeScript

Distributed systems

Cloud-native development

Relational data modeling

Autonomy

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