Own and evolve core data models and metrics
Build and operate foundational data products
Design and maintain shared metric definitions and semantic layers
Work closely with Product, Data Platform, and teams as key consumers
Make pragmatic decisions about modeling standards, architecture, and tooling that balance near-term delivery with long-term maintainability

Requirements

2+ years leading or formally managing data professionals
6+ years building and owning shared, reusable core data models
Familiarity with product usage, and customer data common to SaaS environments
Advanced SQL
Strong Python
Experience with Spark
Comfort working in a modern lakehouse environment (e.g., Databricks)
Experience designing for data quality, reliability, and availability, including workflow orchestration with Airflow or Astronomer
Proven ability to build foundational models and metric definitions
Understanding of performance, cost, governance, security, and compliance considerations for shared data
Ability to partner effectively with Product, Data Platform, Business Analytics, Engineering, and Data Science teams
You know when to ship and when to invest in durability
Interest in AI-assisted development

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythonSparkdata modelingworkflow orchestrationdata qualitydata reliabilitydata availabilitymetric definitionsAI-assisted development

Soft Skills

leadershipcollaborationdecision makingcommunicationpragmatismpartneringproblem solvingorganizational skillsstrategic thinkingadaptability