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.
Atlassian is looking for a Senior Data Engineer to join our Data Engineering team and build world-class data solutions and applications that power crucial business decisions throughout the organization. We are looking for an open-minded, structured problem solver who is passionate about building systems at scale. You will enable a world-class engineering practice, drive the approach with which we use data, develop backend systems and data models to serve the needs of insights, and play an active role in building Atlassian’s data-driven culture. You love thinking about how the business can consume data and then figure out how to build it.
On a typical day, you may be consulted on the information architecture of our data lake and help design and/or optimize the event collection infrastructure. You will be working with different partners to understand the business needs and architect/build the data models, data acquisition/ingestion processes, and data applications that can help address those needs. You have got proven experience working with large-scale, high-performance data processing systems (batch and/or streaming) to drive Atlassian’s business growth and improve the product experience. Constantly aiming to optimize the data pipelines/infrastructure to provide data with quality and trust. As the data domain specialist, you will be partnering with our technology teams, analytical teams, and data scientists across various initiatives.
You’ll lead a problem end-to-end, so those skills will come in handy not just to collect, extract, and clean the data, but also to understand the systems that generated it, and automate your analyses and reporting. On an ongoing basis, you’ll be responsible for improving the data by adding new sources, coding business rules, and producing new metrics that support the business. Requirements will be vague, and Iterations will be rapid. You will need to be flexible and take smart risks.
More about you
As a senior data engineer, you will have the opportunity to apply your strong technical experience with building analytics data models that support a broad range of analytical requirements across the company. You will work with extended teams to continually evolve solutions as the business processes and requirements change. You enjoy working in a fast-paced environment and you can take vague requirements and transform them into proven solutions. You are motivated by solving meaningful problems, where creativity is as crucial as your ability to write code.
On the first day, we’ll expect you to have:
A BS in Computer Science or equivalent experience with 5+ years professional experience as a Sr. Data Engineer or in a similar role.
Strong programming skills using Python & Java (good to have).
Experience in designing data models for optimal storage and retrieval to meet critical product and business requirements.
Experience building scalable data pipelines using Spark maximizing Airflow scheduler/executor framework or similar scheduling tools.
Experience working in a technical environment with cutting-edge technologies like AWS data services (Redshift, Athena, EMR) or similar Apache projects (Spark, Flink, Hive, Kafka).
Ability to understand and influence logging to support our data flow, architecting logging framework & standard methodologies where needed.
Understanding of Data Engineering tools/frameworks and standards to improve the productivity and quality of output for Data Engineers across the team.
You’re well versed in modern software development practices (Agile, TDD, CICD) and how they can apply to data engineering.
Improve data quality by using & improving internal tools/frameworks to automatically detect DQ issues.
Working knowledge of relational databases and query authoring (SQL).
Experience with SaaS companies
We’d be super excited if you have:
Experience with ML engineering.
Followed a Kappa architecture with any of your previous deployments
Domain knowledge of Order Management, Entitlement, Billing, Financial and People System.
More about the team
The data engineering team is responsible for running multiple analytical data models and data pipelines all across Atlassian, including finance, growth, product analysis, customer support, sales, marketing, etc. There are endless growth opportunities. We maintain Atlassian’s data lake and build creative and reliable analytics data models that provide a unified way of analyzing our customers, our products, our operations, and interactions.
You’ll be joining a team that is inquisitive and very direct. We ask hard questions and challenge each other to constantly improve our work. We are self-driven but collaborative. We’re all about enabling growth by delivering the right data and insights in the right way to partners across the company.
Our perks & benefits
To support you at work and play, our perks and benefits
include ample time off, an annual education budget, paid volunteer days, and so much more.
The world’s best teams work better together with Atlassian. From medicine and space travel, to disaster response and pizza deliveries, Atlassian software products help teams all over the planet. At Atlassian, we’re motivated by a common goal: to unleash the potential of every team
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone’s perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.