Design and build resilient, secure cloud data platforms for a premier financial services client. Lead the architecture of enterprise ELT/ETL pipelines using Azure Data Factory and automate deployments via Azure DevOps. Requires proven commercial experience in the Microsoft Azure data stack, advanced SQL proficiency, and eligibility for 482 visa sponsorship.
Key Highlights
Key Responsibilities
Technical Skills Required
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Job Description
We are partnering with a premier financial services client to execute a major enterprise data modernisation program and build resilient, secure cloud data platforms. We are seeking an experienced Azure Data Engineer to represent our organisation and take technical ownership of designing, automating, and scaling high-throughput data integration pipelines within the Microsoft Azure ecosystem.
In this role, you will bridge modern cloud data architectures and regulatory compliance within our client’s financial ecosystem. You will be instrumental in architecting enterprise ELT/ETL pipelines using Azure Data Factory (ADF), automating deployments through Azure DevOps, and delivering performant data platforms across Azure Data Lake, Azure Synapse Analytics, and Azure SQL Database.
As the employer of record, we provide full visa and migration support for qualified engineering talent deployed to our clients:
- 482 On-Hire Sponsorship Transfers: Fully supported for qualified candidates currently in Australia on an existing 482 visa looking to transfer sponsorship to work with our clients.
- New 482 Visa Sponsorship: Available for qualified candidates meeting commercial experience and technical requirements.
- Temporary & Working Visa Holders: Open to all working visa holders seeking a direct pathway to employer sponsorship.
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- Pipeline Architecture & Build: Lead the design, build, and optimisation of resilient, scalable batch and event-driven data pipelines using Azure Data Factory (ADF).
- End-to-End CI/CD Automation: Implement and manage automated CI/CD deployment pipelines for database objects, ADF components, and data assets using Azure DevOps.
- Data Warehousing & Storage: Configure and maintain structured and semi-structured storage layers across Azure Data Lake Storage (ADLS Gen2), Azure Synapse Analytics, and Azure SQL Database.
- Performance Tuning & SQL Engineering: Author complex, high-performance SQL queries, stored procedures, and transformations while optimising compute consumption.
- Data Quality & Governance: Enforce data validation frameworks, lineage tracking, and strict banking-grade security/access controls across all integration points.
- Stakeholder Collaboration: Partner directly with data analysts, enterprise solution architects, and business domain leads to support reporting, analytics, and modernisation milestones.
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- Azure Data Platform Expertise: Proven commercial experience as a Data Engineer delivering solutions across the core Microsoft Azure data stack.
- ADF & ETL/ELT Mastery: Deep, practical knowledge of building and orchestrating complex pipelines using Azure Data Factory.
- Automation & DevOps: Solid commercial track record managing deployments and version control with Azure DevOps (YAML / Git).
- Advanced SQL: Exceptional SQL proficiency with hands-on experience tuning queries, schemas, and stored procedures in relational or analytical databases.
- Modern Data Frameworks: Solid understanding of data lake patterns, dimensional modelling, and modern data engineering methodologies.
- Location Requirements: Currently residing in Australia with valid work rights or eligibility for 482 visa sponsorship/transfer.
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- Experience in banking, financial services, or other highly regulated environments.
- Hands-on experience with Infrastructure as Code (IaC) using Terraform or Bicep in Azure.
- Exposure to business intelligence and reporting tools (Power BI or legacy BI platforms).
- Familiarity with PySpark, Azure Databricks, or Microsoft Fabric.
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