Data Engineer - Senior Analyst / Manager

Job Description

Management Level Manager Job Description & Summary Kia ora, Innovate. B uil d. Reinvent . Make your tech skills count at PwC New Zealand. At PwC, our purpose is clear: to build trust in society and solve important problems. Join our diverse w hān au of experts and be supported with coaching, flexibility, and a culture where you truly belong. Here, you’ll work with world-leading technology - including A.I. - bringing your people- focused skills and experience to deliver outcomes that matter. This i s a place to keep growing. You’ll learn from the best, take on meaningful challenges, and make a lasting impact for our clients, our communities, and Aotearoa. Ngā K ōrero mo tēnei tūranga / About the role We’ re look ing fo r eith er Senior Analysts or Managers to join our Risk Services team in Pōneke / Wellington or Tāmaki Makaurau /Auckland. Your day-to-day could include: Monitor and improve data quality by designing and implementing automated validation rules, performing ongoing data profiling, and executing data cleansing routines to ensure accuracy, completeness, and reliability. Develop, maintain, and continuously refine comprehensive documentation covering data pipelines, data models, solution architecture, and end-to-end data flows to support transparency, scalability, and knowledge sharing. Diagnose, troubleshoot, and resolve complex data pipeline failures, integration issues, and system performance bottlenecks, ensuring high availability and optimal performance across data platforms. Proactively evaluate and adopt emerging Azure data services, industry best practices, and modern engineering patterns to enhance platform capability, security, and efficiency. Collaborate closely with business stakeholders, data analysts, engineers, and product teams to gather requirements, translate them into technical solutions, and deliver robust, scalable, and high-quality data products. Implement CI/CD practices and Infrastructure as Code (e.g., Terraform/Bicep) for deploying and maintaining scalable data infrastructure. Design and optimise data pipelines using Azure services such as Data Factory, Databricks, Synapse, or Event Hub. Ensure data governance by enforcing metadata standards, lineage tracking, and access controls. Ngā pūkenga kei a koe / Skills and experience Minimum 5 years’ experience as a Data Engineer with a strong focus on Azure cloud data services, ideally within a professional services or consultancy environment. Hands -on experience with Data Governance and Management tooling (for example, Informatica , Collibra , etc), including data integration, workflow orchestration, and performance optimisation . Proven ability to design, build, and optimise scalable, secure data pipelines using Azure Data Factory and complementary Azure services such as Databricks, Synapse Analytics, Data Lake Storage, and Event Hub. Strong documentation practices, with the ability to produce clear and maintainable technical documentation covering data processes, arc

Required Skills