OverviewWhat you’ll do
Build and maintain data pipelines that extract, transform, and load live product data into research-ready formats (Postgres, data lake, or analytics warehouse)
Design and optimize data models tailored to the recurring analyses behind our AI Impact Reports, DX Core 4 benchmarks, and industry-facing publications
Collaborate closely with the research and engineering teams to understand analytical requirements and translate them into scalable, reproducible data infrastructure
Ensure data quality and consistency: you care about definitions, edge cases, and making sure the same question gets the same answer every time
Support ad hoc data pulls for time-sensitive research and cross-functional requests from Sales, Customer Success, and product teams
Document everything - schemas, transformation logic, data dictionaries, and pipeline dependencies so that analysts and researchers can self-serve confidently
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
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.
This role may also be eligible for benefits, bonuses, commissions, and equity.
Pay Ranges
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: $167,400 - $218,550
Zone B: $150,660 - $196,695
Zone C: $138,942 - $181,397
Qualifications
What we’re looking for
Strong SQL skills: you can write complex queries, optimize performance, and model data for analytical workloads
Hands-on experience with Postgres or similar relational databases, including working with semi-structured data (JSONB, nested fields)
Experience building and maintaining ETL/ELT pipelines that move data from production systems into analytics-ready formats
Comfort working with large, messy, real-world datasets: you know how to clean, normalize, and validate data at scale
Strong documentation habits: you write clear schema docs, data dictionaries, and pipeline runbooks without being asked
Self-motivated and reliable: you can manage recurring deadlines (e.g., quarterly reporting cycles) with minimal oversight
Nice to have:
Familiarity with developer tooling data: Git/GitHub/GitLab/Bitbucket activity, CI/CD pipeline metrics, Jira issue data
Exposure to survey data, time-series analysis, or benchmarking methodologies
Why this role
High visibility: The data you shape will underpin reports cited by engineering leaders at the world's largest software organizations
High ownership: You'll own the full data pipeline from raw product data to research-ready datasets.
Meaningful domain: You'll work at the intersection of developer experience, AI measurement, and engineering productivity, a space that's defining how the industry thinks about software development
Research-backed environment: Our team includes the researchers behind the DORA, SPACE, and DevEx frameworks. You'll be building the data infrastructure that makes their work possible
Benefits & Perks
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.