Overview
Our Data Engineering Team is comprised of data experts. We build world-class data solutions and applications that power crucial business decisions throughout the organisation. We manage multiple analytical data models and pipelines across Atlassian, covering finance, growth, product analysis, customer analysis, sales and marketing, and so on. We maintain Atlassian’s data lake that provide a unified way of analyzing our customers, our products, our operations, and the interactions among them.
We’re hiring a Senior Data Engineer, reporting to the Data Engineering Manager based in San Francisco. Here, you’ll 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 help build Atlassian’s data-driven culture. You love thinking about the ways the business can consume data and then figuring out how to build it.
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $163,300 - $217,700
Zone B: $147,000 - $196,000
Zone C: $135,600 - $180,700
This role may also be eligible for benefits, bonuses, commissions, and equity.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
You’ll partner with the data analytics and data scientist team to build the data solutions that allow them to obtain more insights from our data and use that to support important business decisions.
You’ll work with different stakeholders to understand their needs and architect/build the data models, data acquisition/ingestion processes and data applications to address those requirements.
You’ll add new sources, code business rules, and produce new metrics that support the product analysts and data scientist.
You’ll be the data domain expert who understand all the nitty-gritty of our products.
You’ll own a problem end-to-end. Requirements could be vague, and iterations will be rapid
You’ll improve data quality by using & improving internal tools/frameworks to automatically detect DQ issues.
On the first day, we'll expect you to have
BS in Computer Science or equivalent experience with 8+ years as a Senior Data Engineer or similar role
Strong programming skills using Python
Working knowledge of relational databases and query authoring (SQL).
Experience designing data models for optimal storage and retrieval to meet product and business requirements.
Experience building and scaling experimentation practices, statistical methods, and tools in a large scale organization
Experience building scalable data pipelines using Spark (SparkSQL) with Airflow scheduler/executor framework or similar scheduling tools.
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)
It's great, but not required, if you have
Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
Familiarity working with Growth, Product, and engineering teams
Excelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions