About Atlassian Corporate Engineering
Atlassian Corporate Engineering (ACE)is Atlassian's "First and Best" customer. We believe our greater purpose is to help unleash the potential of every Atlassian team. As we think about the biggest opportunities to unleash Atlassian and bring this vision to life, it's clear that we need to unlock corporate and user data we need to run Atlassian. Today, we have an opportunity to better translate data into insights; to unlock data from siloes; to better centralize ownership; and to experiment and drive step-level changes with AI, ML and other cutting-edge tech. We want you to come join us to drive better, faster, and more actionable insights for Atlassian.
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Off-the-shelf solutions will only carry us so far. We have the skills and the business need to build more tools internally AND we benefit from working at Atlassian which gives us the unique ability to build on-top of the company's products suite and with the company's platforms. Let's leverage your experience, passion and skills for Atlassian's advantage; reinforce our ability to execute; and continue to provide world-class (reliable + scalable) solutions.
Overview
This Lead Principal Engineer will drive our Sales, Marketing, Finance, and Support technology landscape forward by leading engineering efforts towards our next generation of applications, building strong partnerships and collaborations across Atlassian, ensuring that our product portfolio is cohesive, consistent, and integrated with the broader Atlassian ecosystem.
The Lead Principal Engineer will be at the center of the work we're doing to build one of the best TEAMs in the world.
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $268,800 - $358,400
Zone B: $242,000 - $322,600
Zone C: $223,100 - $297,500
This role may also be eligible for benefits, bonuses, commissions, and equity.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
- Create a vision for a connected ecosystem, and lead the engineering organization to deliver on a cohesive experience.
- Develop engineering excellence standards and drive adoption of those across the entire organization.
- Support the teams' transformation to data-driven decision making, defining metrics and implementing their measurement.
- Work with dependency teams to develop a plan and roadmap, integrating our products into the broader Atlassian ecosystem.
- Help with hiring and mentoring other engineers on team.
- Act as Technical Lead for a large area, providing leadership to other senior technical leads
- Build relationships with key stakeholders and Engineering leaders across Atlassian.
Basic Qualifications
- BS in Computer Science or related technical field or equivalent experience
- 15+ years of experience developing large-scale distributed systems
- 4+ years of experience providing architectural oversight and technical leadership
- A track record of engineering in successful products
Preferred Qualifications
- Excellent communication skills and a track record of cross-group/cross-discipline collaboration.
- Broad experience architecting, designing, and building large-scale distributed systems supporting high-usage applications.
- Broad knowledge and understanding of SaaS, PaaS, and IaaS with hands-on experience with one or more public cloud offerings (ideally AWS)
- Fluency in any modern object-oriented programming language (e.g., Java, Kotlin, Python, Javascript, go, etc.) and in architecture patterns for distributed systems
- Deep Experience with Storage, both relational and non-relational
- Experience with applied Machine Learning
- Able to drive long-term vision and strategy
- Have strong empathy and a bias for action.
- Quick learner who thrives in an ambiguous environment.