Top Data & Analytics Jobs

Leads Atlassian’s enterprise data governance operating model and trusted, AI-ready data strategy. Owns governance policies, domain ownership, decision rights, stewardship, data quality, catalog, metadata, lineage, and enterprise context architecture. Partners with Privacy, Legal, Security, and Compliance while implementing data contracts, automated classification, policy-as-code, and certification controls. Drives governance adoption across a federated organization and enables agents and applications to consume reliable, governed data.

Lead the technical evolution of Atlassian’s data engineering capabilities by architecting scalable batch and streaming data solutions. Direct complex engineering efforts, improve data quality and productivity, establish technical direction, and coordinate implementation across teams. Mentor and coach data engineers while partnering cross-functionally to support data-driven business decisions and long-term platform scalability.

Build and manage scalable data systems, including metric definition, logging instrumentation, data ingestion, architecture, modeling, transformation, quality, governance, visualization, and reporting. Partner with product, analytics, data science, and other data teams to improve product insights, engagement, efficiency, and strategic decision-making.

Data Engineering Interns will define metrics, instrument logging, ingest and model data, transform datasets, ensure data quality and governance, and support visualization, reporting, alerting, and scalable systems. They will partner with product, analytics, and data consumers to improve product engagement, efficiency, costs, and strategic decision-making. The 12-week, full-time internship includes technical training, mentorship, and hands-on project experience.

Designs scalable data architectures, ELT/ETL pipelines, data models, quality frameworks, and self-service data platforms. Partners with engineering, product, program, leadership, and data science teams to translate business needs into technical solutions. The role includes end-to-end technical ownership, large-scale batch and streaming data processing, mentoring junior engineers, system optimization, and on-call support for platform stability.

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, canonical datasets, and AI context layers. The role improves data quality and alignment across sales and finance systems, investigates data inconsistencies, leads requirements through UAT and implementation, supports analytics self-service, and partners with cross-functional teams to deliver process improvements and reliable business data.

Design, develop, and own scalable big data and software solutions for Atlassian’s internal data platform. Collaborate with engineers and architects to ship features, uphold coding standards, and improve security, reliability, availability, performance, and operational excellence. Build and deploy services using distributed systems, cloud platforms, and big data technologies while applying data-driven problem solving.

Own the architecture, technical direction, reliability, cost efficiency, and adoption of Atlassian’s analytical data platform. Build foundational ingestion, transformation, orchestration, compute, and consumption components; establish multi-tenant standards and SLOs; and lead cross-team technical initiatives. The role requires hands-on development, distributed systems expertise, batch and streaming architecture design, cloud experience, and mentorship of senior engineers.

Build and maintain ETL/ELT pipelines to move product data into analytics-ready stores (Postgres, data lake, warehouse). Design and optimize data models, ensure data quality and documentation, support ad-hoc research requests, and collaborate with research and engineering teams to enable reproducible analytics.

Lead data engineering architecture and execution for large-scale, low-latency analytics. Own technical direction, ensure operational data quality, design streaming and batch pipelines, mentor engineers, coordinate cross-functional teams, and deliver scalable solutions using Spark, Airflow, and AWS or equivalent data platforms.