Note: The job is a remote job and is open to candidates in USA. Atlassian is a software company whose DX team builds solutions for developer productivity and experience. The Senior Data Engineer will build and maintain scalable data pipelines and models that transform product data into research-ready datasets for AI impact reports, benchmarks, and industry publications. The role also focuses on data quality, documentation, ad hoc research data requests, and collaboration with research and engineering teams.
Responsibilities
- 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
Skills
- 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
- Experience working with SaaS product data, telemetry, or event-driven data
- 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
Benefits
- This role may also be eligible for benefits, bonuses, commissions, and equity.
- Health and wellbeing resources
- Paid volunteer days
Company Overview
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