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KPMG

Global audit, tax, and advisory services

Data Specialist

Data EngineeringConfirmed live in the last 24 hours
Full-timeAuckland, New ZealandNo salary listed

About the Job

Requirements

  • Strong cloud data engineering experience and comfort working across modern data platforms, ideally within the Microsoft Azure ecosystem.
  • Hands-on experience building and supporting data pipelines using technologies such as Azure Data Factory, Databricks, PySpark, Python, SQL, SSIS, or similar ETL/ELT tools.
  • Understanding of traditional SQL Server, SSIS, data warehouse, and operational data patterns, with interest in transitioning workloads into modern cloud-based architectures.
  • Confidence working with SQL Server and Azure SQL, including T-SQL development, stored procedures, views, indexing, relational modelling, and performance tuning.
  • Experience, or a strong interest, in modern platform capabilities such as Databricks, Delta Lake, Unity Catalog, Microsoft Fabric, Power BI semantic models, and governed data products.
  • Experience integrating data from multiple sources, including APIs, files, databases, cloud services, vendor platforms, and internal business systems.
  • Comfort working through platform transition, supporting existing operational processes while helping shape improved engineering, governance, and delivery practices.
  • Experience with Azure DevOps, source control, release processes, and deployment practices.
  • Ability to work with business stakeholders, technology teams, and external vendors to translate requirements into reliable, scalable, and supportable data solutions.

Responsibilities

  • Design, develop, and maintain data pipelines, data integrations, databases, and models supporting analytical solutions.
  • Build and support modern ETL/ELT patterns across cloud data platforms, including Azure, Databricks, SQL, and related Azure services.
  • Integrate and manage data from internal and external source systems, including APIs, files, cloud services, operational applications, and vendor platforms.
  • Develop and support curated data products for semantic models, Power BI reports, downstream integrations, and future AI-enabled consumption patterns.
  • Support operational data workloads, business process automations, reference/master data needs, and integration persistence using relational data platforms where appropriate.
  • Produce and maintain BI reporting solutions, semantic models, and analytics-ready datasets that provide accurate, consistent, and timely insights.
  • Contribute to data governance practices, including data quality, lineage, access control, metadata, sensitivity classification, and documentation.
  • Use Azure DevOps and modern engineering practices to manage code, deployments, releases, and change control.
  • Collaborate with business stakeholders, technology teams, data consumers, and external vendors to understand requirements and deliver reliable, scalable solutions.
  • Monitor, troubleshoot, and improve existing data processes to ensure performance, reliability, security, and supportability.

About the Company

KPMG

Global audit, tax, and advisory services

KPMG is a global network of independent professional firms that provide Audit, Tax, and Advisory services. Its work involves helping organizations verify financial information, manage tax obligations, and solve business problems through advisory support, risk management, and performance improvement. Services are delivered by cross-border teams across a worldwide network, with an emphasis on consistency and collaboration among member firms. KPMG distinguishes itself through its history as a series of international mergers that created a large, integrated firm with a shared global standard and brand, rather than a single locally owned entity. Its goal is to help clients navigate complex regulations, improve performance, and achieve sustainable growth across multiple markets.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
1987

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