Data Analyst

About SafeLease

We're rethinking how P&C insurance is sold in an age of technological change. SafeLease designs, underwrites, and distributes specialty coverage for commercial property owners and their tenants. We control the full stack: product design, tech, and the speed at which we move. We're a profitable insurance business that backs our policies with our own capital, offering flexibility and savings for more than 4,000 properties insured for billions in value.

We're a team of 70, growing over 100% annually, and we've done it without sacrificing profitability or culture. We embrace the newest technologies, move fast together, and operate with the intensity of a small company where every person's work is visible.

If you're looking for a place to sharpen your craft alongside people who take their work seriously, you'll fit right in.

About The Role

We're looking for an Analytics Engineer / Data Analyst to unlock the value of our data assets by transforming and presenting data in a way that drives action. You’ll be a key voice in turning data signals into business decisions.

• Data Modeling & Transformation
• Design, build, and maintain dbt models that transform raw source data into clean, well-documented, analytics-ready tables in Snowflake
• Own the semantic layer — ensuring consistent metric definitions that all stakeholders can trust
• Build and maintain executive and department-level dashboards that communicate performance clearly and without ambiguity
• Partner with stakeholders across pricing/actuarial, sales, business development, and operations to understand reporting needs and translate them into durable, self-serve solutions
• Distinguish between dashboards that inform decisions and dashboards that create noise — and build accordingly
• Conduct deep-dive analyses to explain anomalies, validate hypotheses, and uncover signals in messy data
• Synthesize findings into clear, concise narratives — written, visual, and verbal — appropriate for technical and non-technical audiences
• Proactively identify inflection points in the data and connect them to operational or market causes
• Contribute to strategic decisions by framing tradeoffs with data, not just describing what happened
• Data Quality & Governance
• Instrument data quality checks and alerting so issues surface before they reach decision-makers
• Maintain data dictionaries and lineage documentation that make the platform legible to the broader organization
• Possess strong SQL skills — you write queries from scratch, optimize them, and know when a query is telling you something wrong
• Have hands-on experience with dbt (Core or Cloud) — model structure, ref/source, tests, documentation, incremental strategies
• Be proficient with Snowflake or a comparable cloud data warehouse
• Experience building dashboards in Metabase, Looker, Mode, Tableau, or similar
• Have proven ability to go from a vague business question to a structured analysis to a clear recommendation
• Have strong written communication — your documentation and stakeholder write-ups are as clear as your SQL
• Plus experience in insurance, fintech, or real estate data environments
• Familiarity with property data, underwriting data, or policy/claims datasets
• Experience in Python for data analysis (pandas, notebooks, scripting)
• Experience working in a startup or early-stage data team where you had to build the foundation, not just extend it

Required

• 3–5+ years of experience in analytics engineering, data analysis, or a hybrid role
• Strong SQL — you write queries from scratch, optimize them, and know when a query is telling you something wrong
• Hands-on experience with dbt (Core or Cloud) — model structure, ref/source, tests, documentation, incremental strategies
• Proficiency with Snowflake or a comparable cloud data warehouse
• Experience building dashboards in Metabase, Looker, Mode, Tableau, or similar
• Proven ability to go from a vague business question to a structured analysis to a clear recommendation
• Strong written communication — your documentation and stakeholder write-ups are as clear as your SQL

Plus

• Experience in insurance, fintech, or real estate data environments
• Familiarity with property data, underwriting data, or policy/claims datasets
• Experience in Python for data analysis (pandas, notebooks, scripting)
• Experience working in a startup or early-stage data team where you had to build the foundation, not just extend it

What Success Looks Like

• In your first 90 days, you've learned the data landscape, identified the highest-leverage gaps in our current modeling and reporting, and shipped your first set of dbt models and dashboards into production.
• Stakeholders know who to come to with data questions — and the answers they get are accurate and on time.
• At six months, you've meaningfully improved data reliability and self-serve access across at least two business functions.
• You've led at least one significant deep-dive that influenced a real business decision.
• At a year, you are the person who knows more about how SafeLease data works — end to end — than almost anyone else in the company.
• You're raising the bar for how we define, measure, and act on data, and you're doing it in a way that makes the whole team better.

Why SafeLease?

• The tech: Our prospects convert fast because we’re solving real problems and delivering serious value to commercial real estate owners.
• The team: We’re a team of seasoned pros and sharp operators who know how to move fast and build smart. High standards, low ego.
• The stability: We’re well-funded, growing fast, and we make sure our team shares in that success with competitive pay and equity.
• The employee experience: We also offer unlimited PTO, full health benefits, flexible work setups, and the kind of culture where people want to show up to do their best work.