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The data engineering team manages several data models and data pipelines across Atlassian, including finance, growth, product analysis, customer support, sales, and marketing. You'll join a team that is smart and very direct. We ask hard questions and challenge each other to constantly improve our work.
Job Responsibility:
Apply technical expertise to build analytical data models that support a broad range of analytical requirements across the company
Work with extended teams to evolve solutions as business processes and requirements change
Own problems end-to-end and on an ongoing basis, 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
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)
A willingness to accept failure, learn, and try again
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