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Atlassian is looking for a Data Engineer to join our Go-To Market Data Engineering (GTM-DE) team, which is responsible for building our data lake, maintaining our big data pipelines/services, and facilitating the movement of billions of messages each day. As a Data Engineer, you'll work on an AWS-based data lake backed by open-source projects like Presto, Spark, Airflow, and Hive.
Job Responsibility:
Help our stakeholder teams ingest data faster into our data lake
Make our data pipelines more efficient
Come up with ideas to help instigate self-serve data engineering within the company
Build micro-services
Architect, design, and enable self-serve capabilities at scale to help Atlassian grow
Requirements:
At least 2 years professional experience as a software engineer or data engineer
A BS in Computer Science or equivalent experience
Strong programming skills (some combination of Python, Java, and Scala preferred)
Experience with data modeling
Experience in modern software development practices (Agile, TDD, CICD)
Knowledge of data warehousing concepts
Experience writing SQL, structuring data, and data storage practices
Experience building data pipelines, platforms, micro services, and REST APIs
Experience with Spark, Hive, Airflow and other streaming technologies to process incredible volumes of streaming data
A willingness to accept failure, learn and try again
An open mind to try solutions that may seem crazy at first
Experience working on Amazon Web Services (in particular using EMR, Kinesis, RDS, S3, SQS and the like)
Nice to have:
Experience building self-service tooling and platforms
Built and designed Kappa architecture platforms
A passion for building and running continuous integration pipelines
Built pipelines using Databricks and well versed with their API’s
Contributed to open source projects (Ex: Operators in Airflow)
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