Senior Data Engineer
at Atlassian
Remote, Americas | Remote, Remote | Austin, United States | Mountain View, United States or Remote | New York, United States | Seattle, United States | Washington DC, United States | San Francisco, United States, remote, senior, 6+ years
seen 33d ago
- Airflow
- Scala
- DynamoDB
- Machine Learning
- Redshift
- SQL
- Git
- CI/CD
- MongoDB
- Bitbucket
- Spark
- Databricks
- Postgres
- Python
About the role
Analytics & Data Science | Remote, Americas | Remote, Remote | Austin, United States | Mountain View, United States or Remote | New York, United States | Seattle, United States | Washington DC, United States | San Francisco, United States
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Working at Atlassian
Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
What you would do
Our Product DE organization is looking for a Senior Data Engineer reporting to the Senior Data Engineering Manager. You will be responsible for designing premier data architecture and solutions that drive strategic decision-making. Beyond technical execution, you will collaborate with business stakeholders to translate operational needs into technical requirements and spearhead initiatives to improve overall system efficiency.
* Partner across engineering organizations to spearhead and execute high-impact, company-wide initiatives,
* Mentor and upskill junior engineers, fostering a culture of technical excellence and continuous growth.
* Collaborate with leadership, product engineers, program managers, and data scientists to deeply understand and prioritize business data requirements.
* Leverage deep technical expertise to design and architect scalable, high-performance data solutions.
* Develop, launch, and optimize highly efficient, reliable ELT/ETL pipelines capable of processing both large-scale and specialized datasets.
* Intelligently design robust data models optimized for high-speed storage, accessibility, and downstream retrieval.
* Implement and deploy rigorous data quality frameworks to guarantee data accuracy, freshness, and trust.
* Maintain full technical ownership of the end-to-end data engineering lifecycle for your team's solutions.
* Participate in the team’s on-call rotation to ensure platform stability and support operational health.
* Partner with software engineering teams to design and build next-generation data systems that enable rapid, self-service data consumption.
Read from atlassian.com, last seen 5d ago.