Data Analytics Manager, Roofr

• 5+ years of experience in data roles, with at least 1–2 years managing a technical team
• Strong technical skills in SQL, DBT, and orchestration tools like Airflow
• Experience with modern data stacks (e.g., Snowflake, Redshift, BigQuery) and ELT tools (Stitch, Fivetran, Airbyte)
• Proficiency in data visualization and BI tools (Metabase, Sigma, Looker, or similar)
• Familiarity with Python or R for scripting and data science workflows
• Solid understanding of experimentation, forecasting, and statistical analysis
• Proven ability to drive cross-functional alignment and communicate clearly with technical and non-technical stakeholders
• Passionate about building clean, scalable data infrastructure and enabling data-driven decisions
• Curious: You ask “why” often and dig deep to find the real story behind the data
• Wise: You balance speed and scale, knowing when “good enough” beats perfect
• Technical: You’re comfortable rolling up your sleeves, writing/reviewing a DBT model or debugging a DAG
• Collaborative: You work well across teams and translate data into action

Desirable

• As an Engineer in an early stage and high growth company, you’ll play a critical role in turning raw data into insights that shape product decisions, drive strategy, and improve the customer experience
• You’ll have a direct impact on how we use data to grow, and help influence the roadmap for how analytics evolves at Roofr
• We’re looking for a hands on Data Analytics Manager to lead and scale our growing data function across data engineering, analytics, and data science
• This is a hands-on leadership role for someone excited to define and execute a modern data strategy in a high-growth environment
• You will manage a small but high-impact team and own the full data lifecycle, from ELT pipelines and data modeling in DBT, to dashboarding, experimentation, and predictive modeling
• You’ll work cross-functionally with Product, Engineering, Marketing, and Operations to ensure the business is empowered with clean, trustworthy, and actionable data
• Lead, mentor, and grow a small, multidisciplinary data team (data engineers, analysts, data scientists)
• Define, refine and implement best practices for data modeling, transformation (DBT), orchestration (Airflow), and testing
• Own the data stack and architecture (e.g., Snowflake, DBT, Metabase/Sigma, Stitch)
• Collaborate with stakeholders to define KPIs, build dashboards, and provide strategic insights
• Drive data governance, quality, documentation, and metric standardization
• Guide the development of data products and experimentation frameworks (A/B testing, churn prediction, etc.)
• Partner with leadership to align data strategy with business objectives
• Stay up to date on modern data tooling and recommend improvements to scale infrastructure and processes