Director , Data

Little more about the team:

As the Director of Data, you will be the head of Honeycomb’s data engineering and data analytics functions, responsible for creating and executing our data vision and strategy. You will lead a talented team of data professionals, fostering a data-driven culture and ensuring that insights are effectively integrated into the Company’s decision making process. You’ll also work closely with partners around the company to build and deploy AI technology that leverages our data layer, helping to drive sensible, sustainable patterns for AI-enabled insights. This team currently includes both data engineers as well as our newly forming data analytics group. 

What you’ll do in the role:  

• 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.
• AI + data platform: you understand that at the end of the day, insights and data-informed decisions are what really matter, and the tools we use may change. You have a vision and strategy for how we can sensibly use AI tooling to enable faster access to insights around the company with a sustainable, solid architecture.
• 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.
• Bring a “devtools” perspective to internal data products: obsessive focus on usability, documentation, discoverability, reliability, and iteration speed.

• 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).
• Establish strong governance without slowing teams down: data quality, lineage, access controls, privacy/security practices, and clear ownership.
• Build confidence in the numbers by creating a single source of truth for core metrics and enforcing consistency end-to-end.

What you’ll bring to the role:

• 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.