Principal Technical Data Scientist at Atlassian

Working at Atlassian
Atlassian can hire people in any country where we have a legal entity. Assuming you have eligible working rights and a sufficient time zone overlap with your team, you can choose to work remotely or from an office (unless it’s necessary for your role to be performed in the office). Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Your future team
We're looking for a Data leader with business instincts and analytics mastery that has led projects improving data science efficiency. You are someone that is passionate about applying these skills to increase data quality, reduce the need for data scientists to perform data engineering tasks and love working across the organization to create the proper data layer to increase data science productivity.
You will be reporting to our Head of Experimentation.
What you'll do
Draw on your expertise in understanding software development lifecycle and developer productivity to think about what are data and insights features that we should ship to our internal data science customers to influence the way they work.Partner with the data engineering and platform teams to Identify and support a short, medium and long-term portfolio of projects that improves data assets used across data science.Envision, scope, and lead projects by collaborating with partners, software and data engineering leaders, and data scientists.Guide the creation of tools that allow a centralized data framework that improves the efficiency, quality and capabilities of all data analysts and scientists.Oversee business case development, data requirement gathering (including metrics and definitions), establishing acceptance criteria, QAing, and testing for new transformational data products from start to finish to ensure everything is implemented and validated.Work across marketing and product to develop monitoring and action plans across the data quality lifecycle (instrumentation → transformation → data/metrics/segments)Lead, coach, and build solutions from within a center of excellence.Collaborate with the Business Intelligence team to define and achieve standard segment and metric definitions and governance.Contribute into overall Data Science team OKRs.Be part of building an outstanding analytics culture at Atlassian. Leading by example, through education and creation of self-service tools, to make a lasting change in how data is used to make decisions.Guide demo sessions and education roll out for new data products and features to ensure adoption and usage.
Your background
10+ years of experience with a combination of data science, analytics and data engineering experience.Experience working with software and data engineering teams, an understanding of the software development. lifecycle, what drives software team to succeed and exposure to typical software engineering tools (e.g. Jira, SCM, CI/CD systems).Expertise in data modeling, (e.g. SQL, Python), knowledge of cloud data environments (e.g. AWS), and experience with DBT, data ETLs, and UAT processes.An Agile development mindset, appreciating the benefit of constant iteration and improvement. A very high bar for output quality, while balancing "having something now" vs. "perfection in the future".Experience applying your analytics skills to identify and lead projects that have had impact on strategic and product roadmap decisionsA very high bar for output quality; with experience coaching teams to balance thoughtfulness, perfection and speed.Experience in at least one visualization tool (e.g. Tableau, R-Shiny, dash, Microstrategy)Comfort explaining complex concepts to diverse audiences (such as Product Managers, Designers, Engineers), and creating compelling stories.Project management and prioritization experience; preferably with Data Engineering, Product Management, and Software Engineering teams.