$120K - $170K/yr

Other

Medical, Dental, Vision, Retirement, PTO

This job posting has expired and is no longer accepting applications. Check out similar jobs


Job description

Data Analyst

Chicago or New York

Honeycomb

At Honeycomb, we're reshaping the future of insurance.

In 2025, Honeycomb was recognized by Dun & Bradstreet as "Top 10 Best Start Up Companies to Work For" in Israel and named by LinkedIn as "Top 10 Startups in Chicago".

Honeycomb is a rapidly growing global startup, generously backed by top-tier investors and powered by an exceptional team of thinkers, builders, and problem-solvers. Dual-headquartered in Chicago and Tel Aviv (R&D center), and with 5 offices across the U.S., we are reinventing the commercial real estate insurance industry, an industry long overdue for disruption. Just as importantly, we ensure every employee feels deeply connected to our mission and one another.

With over $55B in insured assets, Honeycomb operates across 20+ major states, covering 60% of the U.S. population and increasing its coverage.

If you're looking for a place where innovation is celebrated, culture actually means something, and smart people challenge you to be better every day - Honeycomb might be exactly what you've been looking for.

Honeycomb Insurance is a modern, data-driven insurance company building smarter ways to underwrite and manage risk.

About the Role

We are looking for a Financial & Data Analyst to join our Finance organization and help us build a scalable, accurate, and automated data foundation. This role bridges Finance, Accounting, and Engineering, ensuring that the data powering our financial models, carrier reporting, billing systems, and management reporting is clean, reliable, and engineered for growth. If you enjoy owning data pipelines end-to-end, solving messy data problems, and enabling business teams to move beyond spreadsheets, this is an opportunity to make a major impact.

Reporting to: Chief Financial Officer

What You'll Do

Data Engineering & Pipeline Development

  • Partner with finance and operations teams to understand their data needs and translate them into reliable data models.
  • Partner with Engineering to validate, QA, and reconcile data from policy admin systems, billing systems, and operational databases.
  • Build and maintain automated pipelines supporting Finance and Accounting (SQL, Python, dbt, or similar tools).
  • Develop data models that make financial and operational data reliable, accessible, and well-structured.

Fronting Carrier & Regulatory Reporting

  • Own the data preparation for monthly reports to insurance partners.
  • Ensure data completeness, accuracy, and alignment across sources (policy, claims, billing, accounting).

Billing System Data Preparation & Cleansing

  • Support a billing system migration/implementation by cleaning, reconciling, and validating large datasets.
  • Work closely with Engineering and Finance to align data with billing schemas and business rules.

Analytics Support for FP&A and Accounting

  • Create data assets enabling self-service dashboards and analytical tools.
  • Monitor the data and ensure strong data integrity.
  • Investigate data anomalies and help Finance understand operational drivers behind performance metrics.
What You Bring

Required

  • 3+ years of experience as a Data Engineer, Analytics Engineer, BI Engineer, or similar role.
  • Strong SQL and Python skills and experience working with relational databases.
  • Experience with a cloud data warehouse — BigQuery preferred
  • Experience building ETL/ELT pipelines (e.g., dbt, Airflow, Fivetran, custom pipelines).
  • Comfort working with messy data, performing cleansing, reconciliation, and QA.
  • Analytical mindset with strong attention to detail
  • Ability to communicate findings clearly to non-technical stakeholders.

Nice to Have

  • Experience in insurance, fintech, or financial services.
  • Experience supporting data-driven processes in Finance, FP&A, Accounting, or similar business functions.
  • Familiarity with financial systems such as ERPs or billing systems.
  • Experience with BI tools like Looker, Power BI and Tableau.
  • Experience leveraging AI to generate SQL and Python scripts.

Who You Are

  • You're a builder who enjoys creating structure in ambiguity.
  • You're the type who spots data issues before anyone else does — then digs until you find the root cause.
  • You love empowering non-technical teams with accurate, reliable data.
  • You thrive in cross-functional work between Finance, Accounting, and Engineering.
  • This role is open to candidates based in New York or Chicago, IL

Benefits

  • Salary: $120,000-$170,000
  • ISO stock options
  • Medical, dental, and vision coverage for you and your dependents
  • HSA with company contributions
  • 401(k) with employer match
  • Flexible time off
  • 10 company-paid holidays
  • Paid family leave



Frequently asked questions

Q: What skills or qualities help someone succeed as a Data Analyst?

A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.

Q: What is the career path for a Data Analyst?

A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.