Role Description We are on the hunt for a Senior Data Engineer with experience in Azure Data Engineering & ideally Fabric for a 3-month contract (extendable). You must be in NZ and have resided here for 5 years+ to be considered for the role (to enable government security clearance). - Manage, support, and deliver the engineering of state-of-the-art technical solutions on Azure Data Platforms. - Lead the hands-on end-to-end planning, provisioning, and implementation of Azure Data services. - Provide infrastructure and automation expertise to uplift, deliver and deploy Data Warehousing, Data Functions and end-to-end data analytics solutions. - Design solutions using Azure Data Factory, Azure Synapse, Azure Data Warehousing, Data Lakes, and App Insights. - Work with business stakeholders to help gather specifications and deliver effective solutions based on an understanding of data domains and technology. - Support data warehousing including manipulation, migration & integration. - Provision, modify, support, and manage complex Microsoft PaaS SQL Server databases as well as high availability environments that include SQL clusters, Always on and Availability Groups. - Migrate on-prem services into Azure cloud platforms. - Log using Log Analytics Workspace & configuration of diagnostic settings. - Support in-house and external engineers with data platform configuration used for data ingestion, manipulation, extraction, and cleansing. Qualifications - Significant design and delivery experience in Azure Data Engineering, ideally including Fabric. - Ability to understand business requirements and design effective solutions using deep Azure data engineering skills. - Expertise in the Azure Data Platform - Microsoft frameworks (Cloud-based analytics), Data Catalog, Data Lineage, ML. - Extensive experience in Azure Data, Azure Data Factory, Azure Data Warehousing, Azure Synapse, Azure Databricks, data modelling, Azure SQL, Big Data, Data Lakes and App Insights and Fabric. - Extensive experience in conventional Microsoft BI technologies such as SSIS, SSRS, SSAS. - Expertise in database concepts: SQL Server, Azure SQL DB/MI and Application Services configuration. - Azure DevOps & Automation, DevOps Integration, DataOps experience. - Knowledge of broader Azure Resources, CI/CD, Azure DevOps, IaC, ETL, CosmosDB, Event Hub, Scorecards, Reporting & Dashboards, Service Oriented Architectures (SOA) and programming. - T-SQL, Hadoop, Spark, Kafka, Python, Scala, Impala, R, Power BI - desirable. - New Zealand citizen or permanent resident with 5+ years in NZ, thereby eligible for government security clearance. - You should be available within 2 weeks for a 3-month contract on a daily rate. - Based anywhere in New Zealand. Benefits - Become part of Australasia's largest Azure engineering practice where you can sharpen your expertise and contribute to the latest innovations in tech and services. - Be part of a company that is leading the way in specialised areas and partners on high profile client projects. - Work with a 13-time Gold, 6-time Microsoft Advanced Specialisation & 5-time Microsoft Solutions Partner (including Modern Work). - Thrive in a team that is always learning, always innovating and making waves on a global scale. - Be part of a supportive working environment that values inclusion, flexibility, diversity and differences. - Work flexibly – we recognise the importance of your overall wellbeing! - Ultimately, we will help you to fear less, achieve more in a fast-paced, innovative and cool environment.

• Design, build, and maintain scalable, fault-tolerant data pipelines (batch and/or streaming) for core business and product data. • Ingest data from diverse sources including APIs, databases, event streams, and third-party services, ensuring high data quality and reliability. • Design and manage data models and storage layers (data warehouses, data lakes) that support analytics and downstream use cases. • Partner with analytics, product, and engineering teams to deliver clean, well-documented datasets that enable self-service analytics and experimentation. • Implement monitoring, logging, and alerting to ensure pipeline reliability, performance, and cost efficiency. • Enforce data governance best practices, including access control, privacy, documentation, and data lineage.

• Design, build, and maintain scalable, fault-tolerant data pipelines (batch and/or streaming) for core business and product data. • Ingest data from diverse sources including APIs, databases, event streams, and third-party services, ensuring high data quality and reliability. • Design and manage data models and storage layers (data warehouses, data lakes) that support analytics and downstream use cases. • Partner with analytics, product, and engineering teams to deliver clean, well-documented datasets that enable self-service analytics and experimentation. • Implement monitoring, logging, and alerting to ensure pipeline reliability, performance, and cost efficiency. • Enforce data governance best practices, including access control, privacy, documentation, and data lineage.

• Design and execute SQL-based ETL processes to migrate public safety data from legacy systems • Collaborate with data migration contractors and review technical deliverables • Meet with records management teams to understand legacy data and translate to Mark43 schema • Investigate uniquely formatted source databases for data fidelity • Work alongside deployment, engineering, and product teams to improve migration tools