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Senior Data Engineer

What We’re Building

Honeycomb is the observability platform for teams who manage software that matters. Send any data to our one-of-a-kind data store, solve problems with all the relevant context, and fix issues before your customers find them. Honeycomb is the unified, fast, and collaborative choice for engineering teams who care about customer experience to get the answers they need, quickly. We are passionate about consumer-quality developer tools and excited to build technology that raises our industry’s expectations of what our tools can do for us. We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, as we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023!  If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases.  


Who We Are

We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. 


How We Work

We are a remote-first company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote


The Role

As our very first Senior Data Engineer, you’ll have a unique opportunity to lay the foundation for Honeycomb’s data-driven future. Partnering directly with the Head of Data, you will architect and build a modern, scalable data platform that not only powers our business-critical insights but also sets the standard for data quality and reliability across the organization.


What You’ll Do in the Role:
  • Own the Data Platform: Take full ownership of our Snowflake data warehouse, DBT models, and diverse ingestion platform. You’ll design and maintain end-to-end solutions that enable access to clean, accurate and well-annotated data.
  • Build Scalable Systems: Leverage modern technologies to create robust, production-grade data pipelines and models. Your work will enable rapid iteration and empower teams from R&D to Sales, Marketing, Finance, and beyond to make informed, data-driven decisions and have ownership over their data.
  • Collaborate Across Functions: Work hand-in-hand with engineering, product, sales, marketing, and business stakeholders to translate complex needs into aligned data architectures and actionable insights. Your collaborative spirit will help bridge gaps and foster a culture of shared success.
  • Drive Innovation and Quality: Establish best practices for data quality and reliability by setting meaningful SLO metrics and continuously refining our systems. You’ll have the autonomy to experiment with new technologies and approaches, driving innovation in a fast-paced, evolving environment.
  • Lead with Impact: From planning and deployment to long-term maintenance, you’ll lead critical projects with a keen sense of ownership and strategic vision. Your ability to balance technical excellence with business value will be key to our next phase of growth.

If you are a seasoned data professional with a passion for creating scalable, robust data solutions and enjoy solving complex problems through innovative thinking, we’d love to have you help shape the future of Honeycomb. Join us, and be at the forefront of transforming our data capabilities while making a lasting impact across the entire organization.


What You'll Bring:
  • Extensive data development including expert-level SQL and programming experience in a scripting language (preferably Python)
  • Demonstrated experience with modern data tooling including: MPP Data warehouses (e.g. Redshift or Snowflake (preferred)), DBT Workflow automation (e.g. Airflow, Dagster, Prefect)
  • Experience implementing structured data models, architectures and marts (e.g. Inmon, Kimball)
  • Experience collaborating with data analysts, data scientists and business users with varying levels of data savvy
  • Comfortable working through ambiguous problems - this is our first DE hire so there will be a fair amount of role shaping

Bonus / Preferred experience: 
  • Experience with any of the following: Spark, Scala, Terraform, AWS/K8s, Debezium/Flink
  • Experience managing production-grade data pipelines powering customer-facing applications
  • Exposure to MLOps and supporting ML/AI team’s data requirements
  • Experience working with CRM, Martech and other GTM datasets and systems


What You Get When You Join the Hive
  • Base pay (range) of $170,000 - $200,000 USD, CAD $233,504 - CAD $274,710
  • 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 remote-first mindset and culture (really!)
  • Home office, co-working, and internet stipend
  • 100% employee/75% for dependents coverage for all benefits
  • Up to 16 weeks of paid parental leave, regardless of path to parenthood
  • Annual development allowance
  • And much more...


Please note we cannot currently sponsor or do visa transfers at this time.



Diversity & Accommodations:

We're building a diverse and inclusive workplace where we learn from each other, and welcome nontraditional candidates, and people of all backgrounds, experiences, abilities and perspectives. You don't need to be a millennial to join us, all gens are welcome! Further, we (of course) follow federal and state disability laws and are happy to provide reasonable accommodations during the application phase, interview process, and employment. Please email Talent@honeycomb.io to discuss accessible formats or accommodations. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work; if we can do better - we want to know! 

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What You Should Know About Senior Data Engineer, Honeycomb

At Honeycomb, we’re on the lookout for a talented Senior Data Engineer to join our dynamic team. If you’re ready to make an impact in a remote-first environment, this role could be your next great adventure! As our first Senior Data Engineer, you’ll play a pivotal role in shaping the future of our data platform. You’ll work closely with the Head of Data to architect and build a cutting-edge data platform that underpins our business insights and drives data quality across the organization. Your expertise in SQL and programming, particularly with Python, will be crucial as you take ownership of our Snowflake data warehouse and develop end-to-end solutions for clean, accurate data access. You’ll build scalable systems, collaborate across various teams, and establish best practices to drive innovation and quality. We pride ourselves on fostering a supportive and inclusive culture where you can thrive. Join a talented group of professionals at Honeycomb, where your contributions will shape our data-driven initiatives while enjoying perks like unlimited PTO, development allowances, and a transparent pay structure. If problem-solving and innovative thinking excite you, we can’t wait to see how you can help refine our data capabilities and make a meaningful difference in our projects. See if you’re ready to fly with us at Honeycomb and help us redefine our data landscape!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at Honeycomb
What responsibilities does a Senior Data Engineer at Honeycomb handle?

As a Senior Data Engineer at Honeycomb, you'll take full ownership of the data platform, specifically our Snowflake data warehouse and data ingestion systems. This includes designing and maintaining robust, production-grade data pipelines, collaborating with various teams, and ensuring data quality and reliability through best practices and meaningful metrics.

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What skills and qualifications are required for a Senior Data Engineer at Honeycomb?

To thrive as a Senior Data Engineer at Honeycomb, you’ll need extensive experience in data development, particularly in SQL and Python. Familiarity with modern data tools like Snowflake and DBT workflow automation is crucial, alongside a solid understanding of structured data models and architectures.

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How does collaboration work for a Senior Data Engineer at Honeycomb?

In your role as a Senior Data Engineer at Honeycomb, you’ll collaborate extensively across functions, working closely with teams in engineering, product, sales, and marketing. This collaboration is key for translating complex needs into effective data architectures and actionable insights, fostering a culture of shared success.

Join Rise to see the full answer
What innovative technologies might a Senior Data Engineer at Honeycomb work with?

In the position of Senior Data Engineer at Honeycomb, you'll have the opportunity to experiment with modern technologies such as DBT, Airflow, and possibly tools like Spark and AWS/K8s. This role encourages innovation, making it a dynamic environment for new ideas and approaches to data engineering.

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What is the work culture like for a Senior Data Engineer at Honeycomb?

The work culture at Honeycomb is remote-first and focuses on impact and collaboration. As a Senior Data Engineer, you’ll be part of a responsible and inclusive team, committed to living our values every day while enjoying trust, autonomy, and accountability in how you deliver your work.

Join Rise to see the full answer
Common Interview Questions for Senior Data Engineer
Can you explain the role of a Senior Data Engineer in managing data quality?

In managing data quality, a Senior Data Engineer needs to set meaningful service level objectives (SLOs) and continually refine systems to improve data reliability. Discuss how you assess data quality and the strategies you implement to ensure that all data insights are based on accurate and clean data.

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How do you approach building scalable data pipelines?

When building scalable data pipelines, I prioritize understanding the specific needs of upstream and downstream users. I focus on leveraging modern technologies and best practices to design systems that can accommodate growth without compromising performance. Share examples of technologies you've used in the past.

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What experience do you have with SQL and Python in data engineering?

As a Senior Data Engineer, I’ve utilized SQL for database management and querying, and Python for data processing and automation tasks. Discuss specific projects where these skills were critical to achieving efficiency or solving complex problems.

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Describe a time when you had to collaborate with cross-functional teams?

Collaboration is vital in a data-focused role. I once worked with engineering, product, and marketing to create a data model that met diverse needs. Emphasize your communication strategies and how you ensured alignment among different stakeholders.

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What strategies do you implement to adapt to ambiguous problems in a data project?

In addressing ambiguous problems, I lean on a structured framework that includes gathering requirements, hypothesizing potential solutions, and iteratively testing outcomes. Be ready to illustrate a specific instance where you effectively managed uncertainty.

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How do you ensure that your data architectures are aligned with business needs?

Aligning data architectures with business needs requires a deep understanding of the business objectives. I engage in regular discussions with stakeholders to gather input and refine data models accordingly. Describe how you’ve done this in the past.

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What is your experience with cloud data warehouses, especially Snowflake?

I have substantial experience working with cloud data warehouses like Snowflake, where I have designed schemas and built ETL processes. Discuss the benefits you have leveraged from using Snowflake in your previous roles to enhance efficiency.

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How do you keep yourself updated with the latest data engineering trends?

I maintain my knowledge by following industry blogs, online courses, and attending conferences. Share how you integrate this ongoing learning into your work and how it has positively influenced your projects.

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What do you think are the most critical metrics for data quality?

Key metrics for data quality often include accuracy, completeness, and timeliness. It's important to define these metrics based on specific business contexts. Discuss how you monitor and act on these metrics to ensure data integrity.

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Can you provide an example of a successful data-driven project you've managed?

One successful project I managed involved integrating multiple data sources to create a unified reporting dashboard for sales teams, which improved decision-making significantly. Highlight the problem, solution, and impact in your answer to show your experience.

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Give all software engineering teams the observability they need to eliminate toil and delight their users. Honeycomb was founded by a software engineer (a “dev”) and an infrastructure engineer (an “ops”). We were determined to build a world of sof...

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Full-time, remote
DATE POSTED
March 9, 2025

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