Analytics & Data Science | Sydney, Australia | Remote, Remote | Full-Time
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.
Our Data Engineering Team is comprised of data experts. We build world-class data solutions and applications that power crucial business decisions throughout the organisation. We manage multiple analytical data models and pipelines across Atlassian, covering finance, growth, product analysis, customer analysis, sales and marketing, and so on. We maintain Atlassian's data lake that provide a unified way of analysing our customers, our products, our operations, and the interactions among them.
We're hiring a Data Engineer, reporting to the Data Engineering Manager. Here, you'll 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 help build Atlassian's data-driven culture. You love thinking about the ways the business can consume data and then figuring out how to build it.
You'll partner with the data analytics and data scientist team to build the data solutions that allow them to obtain more insights from our data and use that to support important business decisions.
You'll work with different stakeholders to understand their needs and architect/build the data models, data acquisition/ingestion processes and data applications to address those requirements.
You'll add new sources, code business rules, and produce new metrics that support the product analysts and data scientist.
You'll be the data domain expert who understands all the nitty-gritty of our products.
You'll own a problem end-to-end. Requirements could be vague, and iterations will be rapid.
You'll improve data quality by using & improving internal tools/frameworks to automatically detect DQ issues.
Minimum Requirements:
1. A BS in Computer Science or equivalent experience with 3+ years professional experience as a Data Engineer or in a similar role.
2. Working knowledge of relational databases and query authoring (SQL).
3. Experience designing data models for optimal storage and retrieval to meet product and business requirements.
4. Experience building scalable data pipelines using Spark (SparkSQL) with Airflow scheduler/executor framework or similar scheduling tools.
5. Experience working with AWS data services or similar Apache projects (Spark, Flink, Hive, and Kafka).
6. Understanding of Data Engineering tools/frameworks and standards to improve the productivity and quality of output for Data Engineers across the team.
7. Well versed in modern software development practices (Agile, TDD, CICD).
Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit go.atlassian.com/perksandbenefits to learn more.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
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.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
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