Engineering Manager, Data & Analytics

Karbon is the global leader in AI-powered practice management software for accounting firms. We provide an award-winning cloud platform that helps tens of thousands of accounting professionals work more efficiently and collaboratively every day. With customers in 40 countries, we have grown into a globally distributed team across the US, Australia, New Zealand, Canada, the United Kingdom, and the Philippines. We are well-funded, ranked #1 on G2, growing rapidly, and have a people-first culture that is recognized with Great Place To Work® certification and on Fortune magazine's Best Small Workplaces™ List.

Engineers are expected to balance delivery speed with a strong commitment to quality, meeting agreed timelines while producing reliable, maintainable, and well-tested solutions. Sound judgment in making trade-offs between velocity and long-term sustainability is essential.

Engineering is collaborative by default. Team members are expected to contribute constructively in design discussions, reviews, and planning, communicate clearly about progress and risks, and support shared team outcomes in both hybrid and distributed environments.

Engineers are responsible for building new capabilities while maintaining and improving existing systems. This includes designing scalable solutions, reducing technical debt, supporting operational stability, and contributing to continuous improvement.

A high degree of autonomy is expected. Given clear objectives, engineers should independently translate problems into actionable technical approaches, proactively identify improvements, and continuously expand relevant technical expertise.

Ownership is fundamental. Engineers are accountable for the quality, performance, and customer impact of their work from design through post-release support, and are expected to follow through on commitments.

AI is reshaping how software is built, and we are committed to leveraging it as a force multiplier for creativity, impact, and capability. Engineers are expected to confidently apply strong technical fundamentals while embracing AI tools and approaches to enhance productivity, problem-solving, and innovation. Curiosity, adaptability, and enthusiasm for integrating AI into meaningful product development are essential.

Engineers contribute positively to a culture of professionalism, transparency, low bureaucracy, and mutual respect, strengthening team performance through authenticity, curiosity, and collaboration.

We’re hiring a Data & Analytics Manager who grows high-impact teams that balance efficiency with excellence, value autonomy and creativity, and thrive in a collaborative, inclusive environment.

Team vision: “Enable rapid innovation through a unified data platform”

• Coach and grow engineers through clear expectations, regular feedback, and thoughtful development plans.
• Create an environment where engineers can do focused work, collaborate effectively, and keep improving—without heroics or burnout.
• Help build a strong team culture that values autonomy, accountability, and craftsmanship.
• Help the team thoughtfully adopt AI-assisted tooling across the software delivery lifecycle to improve developer productivity and code quality.
• Lead by example in using AI tools where they add real leverage, and help engineers understand when AI accelerates work—and when human judgment matters most.

• Partner with Product and Design to translate goals into a clear plan, then guide the team through execution in a Scrum cadence (planning, delivery, review, retro).
• Manage a multi-million dollar product, growing our top and bottom line while improving platform stability
• Balance new work, enhancements, bugs, maintenance, and technical debt with sound judgment and transparent trade-offs.
• Improve delivery quality and speed over time by reducing friction, improving clarity, and continuously strengthening engineering practices.

• Champion strong development practices: code reviews that teach, testing discipline, pragmatic documentation, and maintainable implementations.
• Encourage “analytical” thinking - creatively solving data problems for our customers is at the heart of this role.
• Champion “you build it, you own it” - Deliver product while balancing technical health

• Help the team build healthy on-call and operational practices, including ownership, runbooks, sensible alerting, and effective incident follow-up.
• Lead blameless incident reviews focused on learning and systemic improvements.
• Improve observability and system health so the team can confidently ship and support the Core product over time. (This role may include on-call participation in the future.)

• Collaborate effectively across Engineering, Product, Design, and Support.
• Communicate clearly across time zones and contexts—making decisions understandable and durable.

In this role, success typically means:

• Your engineers are growing in skill, confidence, and ownership—and they want to stay on your team.
• The team ships consistently with high quality, and reliability improves quarter over quarter.
• Technical decisions make the analytics product easier to evolve (not harder).
• Cross-functional partners trust your team because expectations, trade-offs, and delivery are clear.

• Data Warehousing: Databricks and Snowflake.
• ELT: Fivetran, DLT, DBT
• Visualisation: PowerBI Embed
• Backend: C# (.NET)

• Previously a Senior+ IC before moving into management (preferably as a data engineer or analytics engineer) .
• 2+ years experience in Engineering Management.
• Proven record leading teams to improve quality and speed through technical + process change.
• Depth in distributed systems and data integrity at scale.
• Skill planning and delivering sprints with Product and Tech Leads, balancing new work, enhancements, bugs, and maintenance.
• Excellent communication across locations/time zones.
• Experience in large scale, multi-cloud data warehousing migrations.
• Degree in CS or equivalent experience.
• Plus if you have accounting domain experience.