Data Engineer

Atlassian is hiring a Data Engineer to build data solutions, backend systems, and data models that support organization-wide decisions and analytics. The role also involves developing scalable data engineering practices and evolving data products as business requirements change.

Responsibilities:

• Build world-class data solutions and applications that power crucial decisions throughout the organization
• You will enable world-class data engineering practices, drive the approach with which we use data, develop backend systems and data models to serve the analytical needs and play an active role in building Atlassian’s data-driven culture
• The data engineering team manages several data models and data pipelines across Atlassian, including finance, growth, product analysis, customer support, sales, and marketing
• As a Data Engineer, you will apply your technical expertise to build analytical data models that support a broad range of analytical requirements across the company
• You will work with extended teams to evolve solutions as business processes and requirements change
• You'll own problems end-to-end and on an ongoing basis, you'll improve the data by adding new sources, coding business rules, and producing new metrics that support the business

Requirements:

• BS/BA in Computer Science, Engineering, Information Management, or other technical fields and 4+ years of data engineering experience
• Strong programming skills using Python or Java
• Working knowledge of relational databases and query authoring via SQL
• Experience designing data models for optimal storage and retrieval to meet product and business requirements
• Experience building scalable data pipelines using Spark (SparkSQL) with Airflow scheduler/executor framework or similar scheduling tools
• Understanding of Data Engineering tools/frameworks and standards to improve the productivity and quality of output for Data Engineers across the team
• Strong ability to partner directly with cross-functional stakeholders (Product, Analytics, Finance, Operations) to translate complex business questions into data-driven insights
• Experience with reporting tools like Databricks and Tableau with a keen eye for visual clarity, data storytelling, and user experience