Principal Data Engineer

<h3>📋 Description</h3> • Atlassian is looking for a Principal Data Engineer to join our Data Engineering Team and play a tech lead & architect role to build world-class data solutions and applications that power crucial business decisions throughout the organization. • Looking for an open-minded, structured thinker who is passionate about building systems at scale. • 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. • Own the technical evolution of the data engineering capabilities and be responsible for ensuring solutions are being delivered incrementally, meeting outcomes, addressing risks and issues. • Establish a deep understanding of how things work in data engineering, direct technical aspects of work across data engineering, and systematically improve productivity across the teams. • Maintain high operational data quality and proactively address performance, scale, complexity, and security considerations. • Drive complex decisions that can impact the work in data engineering. • Set technical direction and balance customer and business needs with long-term maintainability & scale. • Understand and define the problem space, and architect solutions. • Coordinate a team of engineers towards implementing them, unblocking them if necessary. • Lead a team of data engineers through mentoring and coaching, provide consistent feedback to help them manage and grow the team. • Work with counterparts in other departments as part of a multi-functional team, and build this culture in your team. <h3>🎯 Requirements</h3> • Bachelor’s/Master's degree or equivalent in a STEM field with a minimum 5+ Years of Experience in Data Engineering or related field. • 12+ years of experience in a Data Engineer role as an individual contributor. • At least 2 years of experience as a tech lead for a Data Engineering team. • Great communicator and maintain many of the essential cross-team and cross-functional relationships necessary for the team's success. • Experience with building streaming pipelines with a micro-services architecture for low-latency analytics. • Experience working with varied forms of data infrastructure, including relational databases (e.g. SQL), Spark, and column stores (e.g. Redshift). • Experience building scalable data pipelines using Spark using Airflow scheduler/executor framework or similar scheduling tools. • Experience working in a technical environment with the latest technologies like AWS data services (Redshift, Athena, EMR) or similar Apache projects (Spark, Flink, Hive, or Kafka). • Understanding of Data Engineering tools/frameworks and standards to improve the productivity and quality of output for Data Engineers across the team. • Industry experience working with large-scale, high-performance data processing systems (batch and streaming) with a "Streaming First" mindset to drive Atlassian's business growth and improve the product experience. <h3>🏖️ Benefits</h3> • Health coverage • Paid volunteer days • Wellness resources