Senior Sales Analytics Infrastructure Engineer

Atlassian; United States; Hybrid; USD 157,000 - 204,000; Full time

Benefits offered by this job

Health and wellbeing resources

Volunteer days

Community engagement opportunities

Job summary

At Atlassian, we’re seeking a versatile, seasoned sales data analyst or analytics engineer to align data between enterprise go-to-market and finance. You’ll design robust data pipelines and an AI-ready context layer to enable safe AI interactions and scale data across the company.

You’ll collaborate with finance, data engineering, and cross-functional teams to build canonical datasets, deliver high-volume ETL/ELT workflows, and monitor data quality while guiding data-driven decisions.

Qualifications

• 6+ years of experience in Analytics Engineering, Data Engineering, Data Science, BI, or related field.
• Expert level proficiency with SQL and data modeling.
• Proficiency in Python.
• Experience with BI tools (Tableau, Looker) and CRM/ERP systems (Salesforce, Oracle, Netsuite).

Responsibilities

• Design, build, and maintain data infrastructure for analytical workflows.
• Lead development of data products and an AI context layer for scalable analytics.
• Build canonical datasets with high-volume ETL/ELT pipelines.
• Collaborate with finance and data engineering to flag data inconsistencies that affect closing the books.
• Conduct sizing analyses for data infrastructure changes and QA source data quality.
• Own data transformations from requirements to UAT for new data structures.
• Find efficiencies to remove manual processes and improve data accuracy.

Skills

SQL

Data modeling

Python

Analytical thinking

Problem solving

Tools

Tableau

Looker

Salesforce

Oracle

NetSuite

Job description

At Atlassian, we’re seeking a versatile, seasoned sales data analyst or analytics engineer to align data between enterprise go-to-market and finance. You’ll design robust data pipelines and an AI-ready context layer to enable safe AI interactions and scale data across the company.

You’ll collaborate with finance, data engineering, and cross-functional teams to build canonical datasets, deliver high-volume ETL/ELT workflows, and monitor data quality while guiding data-driven decisions.