LawnStarter
LawnStarter
LawnStarter is a B2C marketplace that connects customers with local lawn-care professionals through online ordering and a mobile app. Customers can schedule and manage services such as mowing, fertilization, bush trimming, and weeding, while service providers gain access to customers seeking dependable lawn maintenance. The company operates across multiple locations in the United States and supports small landscaping businesses through its platform.

Analytics Engineering Manager, Data Governance (Brazil Remote)

Lead LawnStarter’s data governance, quality, and business intelligence foundations for its home-services marketplace. Build reliable pipelines, trusted metrics, governed event tracking, and data infrastructure prepared for AI use.

Description

  • Set the company-wide data roadmap and sequence investments in the data platform
  • Create automated checks for data quality and freshness across sources, pipelines, and reporting
  • Maintain lineage and assess downstream impact from production systems through warehouse models and dashboards
  • Manage Lightdash operations, including workspaces, permissions, certifications, naming, rollout, enablement, query performance, and warehouse costs
  • Develop and govern the semantic layer so each metric has one authoritative definition
  • Set standards for Segment tracking, including ownership, event and property dictionaries, review processes, and drift monitoring
  • Control data access for AI tools and keep the warehouse understandable to AI systems
  • Oversee data security, PII processing, retention, and recurring access reviews under US state privacy requirements
  • Build documentation, ownership frameworks, and review practices that support lasting governance
  • Direct incidents through resolution and link production change reviews to downstream impact analysis
  • Begin as an individual contributor, then recruit and manage a Lead Analytics Engineer

Requirements

  • Strong expertise in data systems with a focus on governance
  • Regularly use AI tools such as Claude Code, Copilot, and ChatGPT for quality checks, automation, anomaly investigation, and documentation
  • Have managed hands-on teams while remaining accountable for output, priorities, and time allocation
  • Can write SQL, troubleshoot Airflow DAGs, and configure access permissions
  • Translate stakeholder needs into practical, prioritized product and platform plans
  • Favor automation for recurring data quality checks
  • Can define and uphold standards across engineering and analytics teams
  • Bring hands-on experience across data warehouses and pipeline infrastructure
  • Have credible experience operating a BI tool and company-wide tracking plan
  • Have worked with Redshift, dbt, Airflow, Fivetran, Segment, Lightdash, Tableau, Metabase, or similar tools
  • Understand data quality, freshness monitoring, lineage, semantic layers, event governance, data security and privacy, and AI-ready data practices

Benefits

  • Annual base salary of $75,000–$120,000
  • Fully remote position
  • Flexible paid time off

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