Lead and develop a world-class team across data engineering, analytics, and (as needed) applied data science—creating clarity, psychological safety, and alignment to business goals.
Setting our strategy and operating rhythm (roadmaps, quality gates, on-call/incident patterns where appropriate, metrics, forecasting, etc) working closely with stakeholders to set clear direction and then make progress, balancing speed and sustainability.
Be hands-on early—writing SQL, prototyping models, reviewing PRs, and unblocking critical work—while also shifting leverage to the team as it grows.
Define and execute Honeycomb’s data strategy you will develop and implement a long-term data strategy that aligns with Honeycomb’s business goals, and contribute to short term priorities across all functions to deliver immediate business value.(self-serve dashboards, trusted metrics, instrumentation gaps closed, etc.).
Make insight a product, not a report: build reliable, fast, self-serve analytics that leaders and teams actually use—you will oversee the development of advanced analytics, dashboards, and reports that provide fast, actionable insights to stakeholders across the organization.
Drive data-informed decisions across functions (Product, Engineering, GTM, Finance, People) by translating complex analyses into crisp narratives and concrete tradeoffs.
Partner tightly with Product & Engineering so data directly informs roadmap decisions, customer experience, and feature prioritization.
Evolve our data architecture to be robust, performant, and cost-aware—improving pipelines, warehouses/lakehouses, orchestration, and implementation of ETL/ ELT processes (e.g., dbt, Airflow, or similar).

Requirements

Extensive experience in data analysis, data engineering, or related fields, and have led a high performing team across both data engineering and data analytics disciplines.
Proven ability to thrive in a fast-paced environment, working both independently and as a hands-on team leader.
Proven track record in developing and executing data strategies that drive business outcomes.
Experience with scaling data infrastructure and tools in high-growth environments, with strong proficiency in SQL, data visualization tools (e.g., Mode, Tableau, Looker), and data engineering tools (e.g., dbt).
Solid understanding of data science tools and techniques (Python and related libraries), with the ability to apply them as needed.
Excellent communication skills with the ability to present complex data insights to executive and non-technical audiences.
Exceptional problem-solving skills, paired with a strategic mindset and the ability to prioritize effectively in a scrappy, fast-changing environment.
Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field; or equivalent experience.

Benefits

A stake in our success - generous equity with employee-friendly stock program
It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience
Time to recharge - Unlimited PTO and paid sabbatical
A distributed-first mindset and culture (really!)
Home office, co-working, and internet stipend
Full benefits coverage for employees, with additional coverage available for dependents
Up to 16 weeks of paid parental leave, regardless of path to parenthood
Annual development allowance
And much more...

Applicant Tracking System Keywords

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

Hard Skills & Tools

data analysisdata engineeringSQLdata visualizationdata scienceETLELTPythondbtAirflow

Soft Skills

leadershipcommunicationproblem-solvingstrategic mindsetprioritizationindependenceteam collaborationadaptabilityinsight generationnarrative translation

Certifications

Bachelor’s degree in Data ScienceBachelor’s degree in Computer ScienceBachelor’s degree in Statistics