Senior Engineer, Platform & Data

Join our incredible team of innovators shaping the future of Intelligent GTM Orchestration.

Lean Data pioneered the development of lead-to-account (L2A) matching and routing into an established software category and expanded the capabilities of automated business meeting scheduling.

Today, Lean Data is the intelligent engine that translates buyer signals into insights and drives revenue processes forward. Our platform serves as the connective tissue across GTM systems to manage data quality, workflow, scheduling, and collaboration in even the most complex scenarios.

Our customers’ success is what drives us. We treat their goals like our own. We don’t wait for them to ask. Service is a given. Championing them is the job. When they win, we win.

Our curiosity drives innovation. We question. We challenge. We dig in. We are students of what comes next. The day we stop learning is the day we stop leading.

We’re each empowered to tackle problems and chase ideas. We commit and deliver. What works, we celebrate. What breaks, we solve. Either way, we own it and raise the bar.

Bold is a choice. We build with ambition and make smart bets for our company, our team, and our product. The companies that win the next decade are rewriting their playbook and executing fast. That’s us.

We’re powered by good humans with high expectations and low egos. We bring our unique strengths and diverse perspectives to win. One championship team.

Lean Data’s headquarters are in Santa Clara, California, and the company also maintains an office in Dublin, Ireland.

Hybrid

• OTE $150K – $200K

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 (Type Script 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 Lean Data:

• Lean Data covers employee insurance premiums up to 90%
• Stock options in Lean Data for all full-time employees