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 thinker 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 the ways the business can consume data and then figuring out how to build it.

　　A typical day may involve collaborating with partners, you will design data models, acquisition processes, and applications to address needs. With experience in large-scale data processing systems (batch and streaming), you will lead business growth and enhance product experiences. And will collaborate with Technology Teams, Global Analytical Teams, and Data Scientists across programs.

　　You'll take ownership of problems from end-to-end: extracting/cleaning data, and understanding generating systems. Improving the quality of data by adding sources, coding rules, and producing metrics is crucial as requirements evolve. Agility and smart risk-taking are important qualities in this industry where digital innovation meets partner/customer needs over time.

　　A BS in Computer Science or equivalent experience with 5+ years of professional experience as a Sr. Data Engineer or in a similar role.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.Experience building real-time data pipelines using a micro-services architecture.Experience working with AWS data services or similar Apache projects (Spark, Flink, Hive, and Kafka).Understanding of Data Engineering tools/frameworks and standards to improve the productivity and quality of output for Data Engineers across the team.Well versed in modern software development practices (Agile, TDD, CICD)