Working at Atlassian

Atlassian can hire people in any country where we have a legal entity. Assuming you have eligible working rights and a sufficient time zone overlap with your team, you can choose to work remotely or return to an office as they reopen (unless it’s necessary for your role to be performed in the office). Interviews and onboarding are conducted virtually, a part of being a distributed-first company.

Job Description:

Atlassian is looking for a hands-on Senior Data Engineering Leader to join our Data Engineering and Applications team and build data products and applications that power critical business decisions across the organization and inform the product strategy. We are looking for a forward-thinking, structured problem solver, technical specialist, and talented 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 a cross-functional team of IT, data platform, product engineering, analytics teams, and data scientists to support various initiatives. Requirements may be vague, but the iterations will be rapid, and you must take thoughtful and calculated risks. You are interested in reporting platforms and data visualization.

More about you

You are passionate about technology and data and understand the power of data to influence the future of companies like Atlassian. You thrive on 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 business engagement skills and thrive on building strong partnerships and working relationships with business and analytics leaders at all levels. You have a strong sense of fiscal discipline, manage tight budgets, and drive cost efficiency.

You are an experienced manager with a strong record of attracting and growing data talent through hiring, coaching, 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:

• 12+ years of experience in building and managing data warehouse, data pipelines, and data products
• 8+ years of experience leading data engineering teams
• Strong business acumen with an understanding of business drivers and of how to drive value using data across the organization
• Demonstrated experience in developing strong business relationships and trust with senior business leaders across different functions.
• Prior experience partnering with Analytics and with Data Science teams
• 10+ Years of experience in delivering data and analytics solutions for various domains like Go To Market, Customer support, Finance, People, Commerce, and Engineering
• Experience with solution building and architecting with public cloud offerings such as Amazon Web Services, S3, EMR/Spark/Hive, Presto/Athena
• Proven experience building streaming and batch processing data pipelines
• Experience building pipelines to support Machine Learning workloads
• Experience with test automation, continuous delivery, ensuring high data quality across multiple datasets used for analytical purposes
• Experience in building anomaly detection checks and proactive monitoring of the quality of the data and KPI's at scale
• Solid understanding and experience building Microservices and RESTful APIs
• Experience with Tableau and other BI tools
• Proven experience hiring and mentoring high-caliber, data-focused engineers with diverse technical strengths and backgrounds.
• High-energy self-starter with a passion for data, enjoy working in a fast-paced environment.
• Exceptional communication skills and can translate technical concepts into easy-to-understand language for business partners.
• A graduate degree in Computer Science or a similar subject area

It's great but not required if you have:

• Experience working with Product Engineering teams
• Experience working with Data Governance teams implementing Data management practices
• Experience working for SAAS companies
• Experience with Machine Learning
• Committed code to open source projects