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Principal Sales Infrastructure Analyst, Analytics Engineering

Job in Austin, Travis County, Texas, 78716, USA
Listing for: Atlassian
Full Time position
Listed on 2026-10-16
Job specializations:
  • IT/Tech
    Data Engineering, Data Analyst
Salary/Wage Range or Industry Benchmark: 156600 - 204450 USD Yearly USD 156600.00 204450.00 YEAR
Job Description & How to Apply Below
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.

Overview

We’re looking for a versatile, seasoned sales data analyst or analytics engineer that will focus on driving data alignment (improving business processes and production systems) between enterprise go-to-market and finance. You’ll design clean, robust data pipelines and infrastructure to monitor data drift between systems/applications like Salesforce, Oracle Fusion, Gainsight, and Databricks. As an experienced senior analytics engineer on our team, you’ll help evolve our data stack, champion best practices in data processing + analytics design, and build a robust context layer on top of our data that enables AI agents to interact safely.

Responsibilities
  • Design, build, and maintain data infrastructure that ensures data quality, consistency, and accessibility for analytical workflows
  • Lead the development of data products and an AI context layer that enables analytics and data access to scale across the company
  • Build and maintain canonical datasets by developing high-volume, reliable ETL/ELT pipelines using data lake and data warehousing concepts
  • Partner with finance, data engineering, and other x-functional teams to track and flag data inconsistencies that obscure the company’s ability to accurately close our books
  • Execute sizing analyses for transformational and ad-hoc data infrastructure changes, including well-defined impact analyses to support new and ongoing initiatives and product launches, conducting investigations and QA on source data quality
  • Develop SME-level knowledge and ownership for core system data transformations (owning the requirements → UAT → DE implementation cycle for a new product or data structure)
  • Leverage available tools to find efficiencies and process improvements to help us and our partner teams (deal desk, central analytics) remove manual processes and improve source data accuracy
  • Investigate reported bugs or deficiencies, working with business analysts and data engineering to do UAT/QA on simple bug-fix & feature releases
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  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: $156,600 - $204,450
  • Zone B: $140,940 - $184,005
  • Zone C: $129,978 - $169,694
Qualifications
  • 6+ years of experience in Analytics Engineering, Data Engineering, Data Science, Business Intelligence, or similar field.
  • Expert level proficiency with SQL and data modeling. You know how to architect data models and influence engineering teams to build for scale and consistency
  • Proficiency in a quantitative programming language, preferably Python
  • Experience with BI tools such as Tableau, Looker, and know how to enable self-service analytics
  • Experience with CRM systems like Salesforce or Hubspot and ERP systems like Oracle or Netsuite
  • Understand effective software and analytics engineering practices and can use AI tools to move faster without creating brittle systems, unclear code, or unnecessary complexity.
  • Ability to…
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