Senior Data Analyst

Bridge data and business needs.

Translate requirements into scalable data models.

Design and build data flow systems.

Develop a unified data platform.

Manage the Salesforce partner data model comprehensively.

Implement partner data quality checks and governance.

Build data analytics tools and dashboards.

Drive data quality and hygiene initiatives.

Ensure data accuracy and reliability.

Collaborate with stakeholders on data issues.

Design and implement data products for analytics.

Transform raw data into actionable insights.

Support HR Systems team with data entry.

Assist in preparing and uploading data files.

Own the vision and roadmap for CSM applications.

Translate business needs into clear user stories.

Develop backend features for data management.

Collaborate with cross-functional teams on reliable solutions.

Design and implement data pipelines.

Build secure data warehousing solutions.

Lead technical implementation projects.

Design scalable solutions for clients.

Collaborate with healthcare clients.

Translate data challenges into insights.

Provide strategic insights on customer health and churn.

Conduct GTM lifecycle analysis and forecast key KPIs.

Bridge data and business needs.

Translate requirements into scalable data models.

Lead the GTM Systems & Tools within Revenue Operations.

Manage the revenue tech stack for Marketing, Sales, and Customer Success.

Design scalable data pipelines for CS.

Develop data models for reporting and ML.

Atlassian is hiring a Data Engineer Intern for Summer 2026.

The position is remote and available to candidates in Australia.

Build and maintain end-to-end data solutions.

Collaborate with global teams.

Develop backend and full-stack code for Patreon's core product.

Build user-facing systems for security features like MFA and ID verification.

Develop cloud data processing solutions.

Collaborate with teams on Microsoft technologies.

Define and drive EA strategy across core applications.

Lead the Architecture Review Board and enforce TOGAF standards.

Translate business requests into analysis.

Utilize AI tools for enhanced analytics.

Drive adoption of TiDB solutions.

Collaborate with sales teams.

Optimize the data backend using Snowflake.

Create effective data models and pipelines.

Design and implement data products for analytics.

Transform raw data into actionable insights.

Build and ship full-stack applications.

Design and implement AI agents.

Translate business questions into metrics and deliverables.

Collaborate with cross-functional teams.

Lead development of cross-system features.

Deliver scalable AI-native applications.

Design and develop scalable data models for analytics.

Collaborate with cross-functional teams for insights.

Develop high-quality features with specified technologies.

Set scalable development patterns using AI tools.

Develop analytics capabilities across business units.

Improve development patterns and foundational datasets.

Define and execute data science strategy.

Lead AI/ML initiatives in healthcare/insurance.

Design and maintain marketing analytics data models.

Collaborate with cross-functional teams to define data needs.

Lead the centralized analytics function.

Develop and execute analytics vision and strategy.

Lead the company's analytics function.

Oversee data use cases and analytics platforms.

Define a research roadmap for strategic questions.

Lead quantitative research on user behavior.

Lead a team of product analysts.

Define and drive the analytical vision.

Lead and develop multiple data sub-teams.

Manage Data Lakehouse architecture and tooling decisions.

Design systems for product telemetry and analytics.

Ensure data reliability and scalability.

Lead the analytics engineering team to scale the data warehouse.

Mentor and provide feedback to junior engineers.

Design and maintain scalable data models.

Apply software engineering practices to analytics code.

Own end-to-end data architecture.

Build and manage batch data pipelines.

Lead and develop data teams.

Own and manage Data Lakehouse architecture.

Design and maintain data pipelines.

Optimize SQL queries and data models.

Provide data-driven insights for marketing strategy.

Measure impact of community and advocacy programs.

Lead and develop data teams.

Manage Data Lakehouse architecture.

Provide data-driven insights for marketing strategy.

Measure impact of community and advocacy programs.

Partner with teams for data-driven insights.

Develop scoring models for lead prioritization.

Collaborate with healthcare clients.

Translate data challenges into insights.

Provide data-driven insights for marketing strategy.

Measure community program impacts on adoption and pipeline.