Data Governance & Platform Manager

Role Description

You'll be the first person at LawnStarter dedicated to data governance - the owner of whether our data can be trusted. That means the quality and freshness of our source data, pipelines, and reports; the definitions behind our metrics; the standards behind our Segment event tracking; the health of our Lightdash workspace; the data feeding our machine learning models; and the security of the data itself.

This is a hands-on role. You'll work solo at first, with the Analytics team around you but nobody under you - building automation, writing checks, fixing what's broken, and putting processes in place that scale past you. If the scope grows the way we expect, this becomes the foundation of a team you'd build.

What makes this role different:

• You're first. Governance has been everyone's side job, so what exists today is yours to reshape - keep what works, redesign what doesn't, and your standards become the company's standards.
• Whole-stack ownership. Source data to pipelines to dashboards and ML models - you own trust across the entire chain, not one slice of it.
• A live migration to shape. Lightdash is landing now. You get to set up its permissions, structure, and norms before bad habits form, instead of untangling them later.

What You'll Own:

• Data quality and freshness - automated monitoring across source data, pipelines, and reports; catching upstream schema and source changes before they break anything downstream; running incidents to resolution when they happen.
• Data lineage and impact analysis - a living map from production source to warehouse model to dashboard, and the process that uses it: when a production change is proposed, its downstream impact on pipelines, metrics, and reports gets assessed before it ships, not discovered after.
• Lightdash - administration, workspace structure, permissions, and the rollout itself. Your job is to give the company self-serve autonomy while keeping the workspace tidy enough that people can find and trust what's there.
• The semantic layer - we just shipped it for our most critical metrics: one governed definition per metric, in code. You'll extend definition and mapping to the rest and guard the layer against uncontrolled growth as it scales.
• Event tracking governance - our governed Segment event catalog: reviewing new events against its standards, keeping it matched to what production actually sends, and evolving the guardrails (naming, property dictionary, drift detection) as tracking grows.
• AI data readiness - AI agents query our warehouse every day through Brain, our internal AI toolkit. You'll govern what data AI tools can access and keep the warehouse AI-legible: documented, consistent, and safe for an agent to query and get the right answer.
• Data security and privacy - access controls, PII handling and retention under US state privacy laws, and periodic reviews of who - and which AI tools - can see what.
• The governance system itself - the documentation, ownership models, and review loops that keep all of the above running without heroics.

Qualifications

• Governance is your craft, not your chore. You genuinely enjoy making data systems trustworthy and tidy.
• AI-native. You use AI tools (Claude Code, Copilot, ChatGPT) daily to build quality checks, write automation, triage anomalies, and document as you go.
• A hands-on senior operator. You write the SQL, debug the Airflow DAG, and configure the permissions yourself.
• Automation-first. Your instinct for any recurring check is to build a monitor, not a checklist.
• An enforcer people actually like. You'll hold engineers and analysts you don't manage to standards.

Requirements

• Zero pipeline incidents from unannounced source-data changes.
• Zero freshness incidents - stakeholders never open a stale dashboard.
• Every area of the business manages on official, well-maintained metrics and dashboards.
• Every Segment event has an owner and a standard.
• Governance runs as a system - documented processes that would survive you taking a month off.

Benefits

• Base salary: $75k–$100k/year
• Equity: The whole company makes decisions on the data you'll guard.
• Fully remote: This work needs deep focus, and we trust you to manage your environment.
• Flexible PTO: We focus on results. Take what you need.