Head of Data Engineering

Head of Data Engineering

Working at Atlassian

Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.

Atlassian is looking for an Engineering Leader to join the Data Engineering team and build data products that power product strategy and important decisions across the organization . We are looking for a leader passionate about building systems at scale. You will lead a world-class data engineering practice, shape up technical strategy and data architecture, and develop data products to enable reporting, analytics, data science, machine learning, and AI workloads.

As the data domain specialist, you will partner with IT, data platform, product engineering, analytics teams and data scientists to support multiple programs. This is a remote position and will report to the Head of Engineering.

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: $233,800 - $311,700

Zone B: $210,400 - $280,500

Zone C: $194,000 - $258,700

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.


You are passionate about technology and data and understand the power of data to influence the future of companies like Atlassian. You excel at developing phenomenal data products using modern data architecture, engineering practices, and tools to process, store, and expose governed and trusted datasets and metrics.

You are well-versed in data-driven and data-informed product development and comfortable with the nuts and bolts of software engineering, data engineering, and basic data science.
You have excellent engagement skills and value building partnerships and working relationships with product and analytics leaders at all levels. You have a sense of fiscal discipline, manage tight budgets, and guide cost efficiency.

You have experience managing managers and a record of attracting and growing data talent through hiring, mentoring, and hands-on career development. You foster an inclusive environment where all points of view are welcomed and encouraged.


On your first day, we'll expect you to have:

  • 15+ years of experience in building and scaling data teams with a focus on data strategy, infrastructure planning, architecture, and data products

  • 10+ years of experience leading data engineering teams, experience managing managers of managers, and experience scaling organizations with over 75 engineers across geographies

  • 10+ Years of experience delivering data and analytics solutions for product teams

  • Product sense with an understanding of product drivers and of how to guide value using data across the organization

  • Demonstrated experience developing influential relationships and trust with senior leaders across different departments

  • Prior experience partnering with Analytics , Data Science, Engineering and Product Management teams

  • Experience building Microservices and RESTful APIs

  • Experience implementing DevOps best practices within the data platform, including solutions for CI/CD, data observability, monitoring, and lineage

  • Experience with BI tools like Tableau, Amplitude, and Redash

  • A graduate degree in Computer Science or a similar subject area

It's great but not required if you have:

  • Experience working for SAAS companies

  • Experience with Machine Learning

  • Committed code to open source projects

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