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Engineering Manager, Data & Analytics
Отличная вакансия в стабильной компании с сильной культурой, современным стеком (Databricks, Snowflake) и фокусом на AI. Предлагаются хорошие бенефиты, включая дополнительные выходные и гибкий график.
Сложность вакансии
Роль требует сочетания глубокого технического опыта в Data Engineering (Databricks, Snowflake) и управленческих навыков для руководства распределенной командой. Высокая планка ответственности за продукт и внедрение AI-инструментов повышают сложность позиции.
Анализ зарплаты
Зарплата в объявлении не указана, но для позиции Engineering Manager в Канберре рыночный диапазон составляет от 160,000 до 210,000 AUD в год. Karbon, как глобальный лидер, обычно предлагает конкурентоспособные условия, соответствующие верхней границе рынка.
Сопроводительное письмо
I am writing to express my interest in the Engineering Manager, Data & Analytics position at Karbon. With a strong background as a Senior Data Engineer followed by over two years of engineering management experience, I have a proven track record of leading high-performing teams to deliver scalable data solutions. My experience aligns perfectly with your tech stack, particularly in managing large-scale migrations and working with Databricks, Snowflake, and dbt.
At my previous role, I successfully balanced the delivery of new product features with the necessity of maintaining technical health and reducing debt, much like the 'you build it, you own it' philosophy Karbon champions. I am particularly excited about your commitment to AI-enabled engineering and would welcome the opportunity to help the team thoughtfully adopt AI tools to enhance productivity. I am confident that my technical depth in distributed systems and my focus on coaching and professional growth will make me a valuable asset to your globally distributed team.
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Описание вакансии
About Karbon
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.
Our Technology Team Standards
Balance Speed and Quality
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.
Collaborate Effectively
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.
Build and Maintain Systems
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.
Operate with Autonomy
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 and Accountability
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-Enabled Engineering
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.
Contribute to Team Culture
Engineers contribute positively to a culture of professionalism, transparency, low bureaucracy, and mutual respect, strengthening team performance through authenticity, curiosity, and collaboration.
About the Role
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”
Lead a high-performing, healthy team
- 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.
Deliver meaningful outcomes in Scrum
- 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.
Raise the bar for engineering excellence
- 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
Build operational strength (without creating toil)
- 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.)
Be a strong cross-team partner
- Collaborate effectively across Engineering, Product, Design, and Support.
- Communicate clearly across time zones and contexts—making decisions understandable and durable.
What Success Looks Like
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.
Our Tech Stack!
- Data Warehousing: Databricks and Snowflake.
- ELT: Fivetran, DLT, DBT
- Visualisation: PowerBI Embed
- Backend: C# (.NET)
About You-- What Sets You Apart!
- 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.*
Why Work at Karbon?
- Gain global experience across the USA, Australia, New Zealand, UK, Canada and the Philippines
- 4 weeks annual leave plus 5 extra "Karbon Days" off a year
- Flexible working environment
- Work with (and learn from) an experienced, high-performing team
- Be part of a fast-growing company that firmly believes in promoting high performers from within
- A collaborative, team-oriented culture that embraces diversity, invests in development, and provides consistent feedback
- Generous parental leave
Karbon embraces diversity and inclusion, aligning with our values as a business. Research has shown that women and underrepresented groups are less likely to apply to jobs unless they meet every single criteria. If you've made it this far in the job description but your past experience doesn't perfectly align, we do encourage you to still apply. You could still be the right person for the role!
We recruit and reward people based on capability and performance. We don’t discriminate based on race, gender, sexual orientation, gender identity or expression, lifestyle, age, educational background, national origin, religion, physical or cognitive ability, and other diversity dimensions that may hinder inclusion in the organization.
Generally, if you are a good person, we want to talk to you. 😛
If there are any adjustments or accommodations that we can make to assist you during the recruitment process, and your journey at Karbon, contact us at people.support@karbonhq.com for a confidential discussion.
*At this time, we request that agency referrals are not submitted for this position. We appreciate your understanding and encourage direct applications from interested candidates. Thank you!*
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Навыки
- Databricks
- Snowflake
- Fivetran
- dbt
- Power BI
- C++
- .NET
- Scrum
- Data Engineering
- Distributed Systems
Возможные вопросы на собеседовании
Проверка опыта перехода из разработки в менеджмент и понимания технических основ.
Расскажите о вашем переходе из Senior IC в Engineering Management: как ваш технический бэкграунд в Data Engineering помогает вам принимать архитектурные решения сегодня?
Оценка навыков управления приоритетами в условиях Scrum.
Как вы балансируете между разработкой новых фич, исправлением багов и сокращением технического долга в рамках спринта?
Проверка опыта работы с современным стеком данных и миграциями.
Опишите ваш опыт проведения масштабных миграций данных между облачными хранилищами. С какими основными рисками вы сталкивались?
Оценка готовности внедрять AI в процессы разработки.
Как вы планируете внедрять AI-инструменты в рабочий процесс команды, чтобы повысить продуктивность, не жертвуя качеством кода и критическим мышлением инженеров?
Проверка лидерских качеств и умения развивать таланты.
Приведите пример, когда вы помогли инженеру вырасти профессионально или справиться с выгоранием. Какие инструменты обратной связи вы использовали?
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