Tennis Australia
Tech / AI / Software
SeniorDataEngineer
“Senior Data Engineer at Tennis Australia. Skills: Data Engineering, Azure Databricks, Azure Data Factory, SQL, Python, PySpark. Designing and delivering scalable data integration, analytics and reporting solutions across our data platform. Ownership of data ingestion and processing”
Industry & Context.
proactively identifying and resolving data quality, availability and performance issues
Preparedness to be flexible in regard to working hours and arrangements relating to work associated with Tennis Australia
What They're Looking For.
Must Have
Demonstrated senior-level data engineering capability, delivering and supporting solutions in enterprise, production-grade data and BI environments, hands-on experience with Azure data technologies, including Databricks, Azure Data Factory and Azure DevOps, with the ability to implement and maintain CI/CD pipelines, Proven capability to design and build scalable analytical data solutions, including data warehouses, lakehouse architectures and dimensional data models, Advanced data engineering skills in SQL, Python, PySpark and Databricks SQL, with a focus on performance, reliability and data quality, Confidence balancing project delivery and BAU/support, proactively identifying and resolving data quality, availability and performance issues in production environments, stakeholder engagement, leadership and communication skills, translating business requirements into robust and reliable technical solutions, Ability to apply best practices across cloud security, access control, analytics architecture and data governance, contributing to standards, design reviews and continuous improvement, Hold (or be willing to obtain) a current Police Check and Working with Children Check, Preparedness to be flexible in regard to working hours and arrangements relating to work associated with Tennis Australia
What You'll Do.
Designing and delivering scalable data integration
analytics and reporting solutions across our data platform
Ownership of data ingestion and processing
Contributing to the evolution of our data architecture
Working hands-on with modern cloud technologies to support a high-quality data warehouse and analytics environment
Building reusable data processing frameworks and architectural approaches that scale with the organisation’s data and analytics needs
and evolve modern data engineering solutions on Microsoft Azure
with a focus on Azure Databricks
Azure Data Factory (ADF)
and Azure Data Lake Storage (ADLS)
Develop and maintain reliable
secure and high‑performing data pipelines
Develop robust data transformations using PySpark
and maintain curated analytical and dimensional data models aligned to TA BI
Manage data ingestion and onboarding of new data sources and partners
Ensure ongoing data quality
reliability and performance across production data and analytics environments
How You'll Work.
Team & Collaboration
Working closely with engineers, analysts and business stakeholders; Collaborate with data engineers, analysts, and stakeholders
Communication Scope
stakeholder engagement; communication skills; translating business requirements into robust and reliable technical solutions
Process & Methodology
Balancing project delivery and BAU/support
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