This is a fantastic opportunity for a Senior Data Engineer - Azure to join a growing data and technology team delivering enterprise-scale analytics, AI, and data platform initiatives.
You'll play a key role in building modern data solutions that drive better business decisions, improve operational performance, and support innovation across the organisation. This is a hands-on senior role suited to someone who enjoys solving complex data challenges, shaping technical solutions, and working with modern cloud technologies - specifically PySpark and Azure Data Factory in a highly visible setting.
This is: what you'll do
Core Pipeline & Data Engineering:
Design, build, and maintain scalable enterprise data pipelines using PySpark, Python, SQL, and Azure Data Factory to drive batch and near real-time data solutions.
Platform Architecture:
Design and optimise cloud-based data platforms across Bronze, Silver, and Gold data layers aligned to enterprise standards.
Enterprise Integration:
Ingest and integrate data across major business systems—including SAP, Salesforce, and Denodo—via APIs, ODBC/JDBC, and file-based transfers.
AI & Science Partnership:
Partner closely with Data Scientists to operationalise machine learning models, feature engineering pipelines, and Generative AI use cases.
Quality & Best Practices:
Drive automation, DataOps, CI/CD, data quality frameworks, and governance across the data landscape.
Production Support & Troubleshooting:
Perform root-cause analysis and resolve complex data, pipeline,



and source-system integration issues within production environments.
This is: what you'll need
Experience:
5-7+ years of hands-on experience delivering enterprise-scale data engineering and integration solutions.
Core Tech Stack:
Strong, expert-level hands-on experience with PySpark and Azure Data Factory (ADF).
Programming & Querying:
Advanced proficiency in Python and SQL.
Cloud & Platform Mastery:
Proven experience building and supporting cloud-based data platforms (experience with Microsoft Fabric, Databricks, Delta Lake, or Azure Synapse is highly regarded).
Enterprise Integration:
Demonstrated capability integrating complex enterprise platforms (SAP, Salesforce) using REST APIs and ODBC/JDBC patterns.
Data Modeling & Architecture:
Solid understanding of data warehousing, dimensional modeling, and modern data engineering practices (CI/CD, Azure DevOps, Git, DataOps).
Stakeholder & Delivery:
Strong communication skills with the ability to bridge technical requirements and business outcomes in an Agile environment.
This is: the perks
Join a business investing heavily in data, analytics, and AI capability.
Work on enterprise-scale platforms, high-impact transformation initiatives, and modern Azure environments.
High-impact role with strong visibility across the business and technical teams.
Opportunity to shape data platform capability, design reusable frameworks, and drive engineering standards.
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📌 Senior Data Engineer - Azure (Melbourne)
🏢 Natural Selection Group
📍 Melbourne