Top Data Engineer Jobs in New Zealand

Develop and maintain scalable Python applications, APIs, microservices, and data pipelines using PySpark and Airflow. Deploy and operate solutions on Azure with Docker and Kubernetes, implementing monitoring, logging, alerting, and production support. Collaborate with product managers, data scientists, and engineering teams on global projects while contributing to coding standards, architecture, testing, documentation, and Agile delivery.

Own and develop production data pipelines across SAP, retail, logistics, and marketing systems. Design scalable architectures, migrate legacy pipelines, model data for analytics and AI, and implement testing, observability, alerting, governance, and automation. Partner with business stakeholders to create trusted datasets, improve platform infrastructure, and mentor junior engineers. The role requires strong SQL and Python, dbt, cloud data platform experience, orchestration, production debugging, and end-to-end ownership.

Leads the design, development, deployment, and continuous improvement of scalable Azure data solutions. Builds cloud-native platforms using Spark, Databricks, Python, and SQL; establishes CI/CD, testing, automation, and DevOps practices; resolves complex technical issues; collaborates with global stakeholders; and mentors engineers while contributing to platform architecture and roadmap decisions.

Design, build, and optimise scalable data pipelines, products, architectures, and platforms. Ensure data reliability, security, quality, governance, performance, and accessibility while translating stakeholder needs into technical solutions. Collaborate with analytics, reporting, AI, and digital teams; contribute to strategic data initiatives; and mentor junior engineers.

Lead the design and development of cloud-based data platforms, pipelines, ETL/ELT processes, data models, warehouses, and lakes using Azure and Databricks. Build integrations, optimize performance, implement governance, monitor pipelines, resolve issues, and create Power BI reports. Collaborate with product managers and technical teams to deliver scalable, reusable data solutions and document processes.

Engineer and operate Meridian’s Azure Databricks data platform and supporting Azure infrastructure. Ensure secure, reliable, highly available platform services, delivered through infrastructure as code. Responsibilities include Azure networking, identity, storage, Key Vault, monitoring, governance, platform security, Terraform, source control, CI/CD, and technical ownership of shared platforms supporting data and AI workloads.

Lead the design and development of cloud-based data platforms using Azure and Databricks. Build and optimize ETL/ELT pipelines, data models, warehouses, lakes, and integrations; implement governance, monitoring, and troubleshooting; and create Power BI reports. Collaborate with product managers and cross-functional teams to deliver scalable, high-quality data solutions, while documenting processes and applying coding and DevOps best practices.

Design, build, and maintain reliable AWS data pipelines, orchestration, and warehouse models supporting analytics, BI, and customer reporting. Resolve data issues at their root, establish testing, monitoring, and documentation practices, and use AI where helpful. Mentor junior engineers and collaborate with Product, Engineering, Customer, and Finance teams. The role also involves data quality, event-driven integrations, security, governance, and multi-region systems.

The Senior Data Engineer will design, build, and maintain scalable data pipelines, collaborate with teams, ensure data quality, and evolve data practices.

Lead enterprise data engineering initiatives, designing scalable pipelines, data warehouses, integrations, and cloud data platforms. Translate business objectives into secure, high-quality data solutions while overseeing architecture, modelling, optimisation, governance, and master data management. Collaborate with data scientists and AI engineers to operationalise analytics and machine learning, mentor team members, and promote technical excellence and continuous improvement.

The Azure Data Engineer role involves designing and implementing data solutions on Azure, working with multiple projects, and consulting with clients. Key responsibilities include developing data architectures, continuous integration practices, and engaging in training and continuous improvement initiatives.

The Senior Data Engineer builds real-time data pipelines, implements data mesh architectures, and engages with clients to enhance data interactions, focusing on creating impactful data solutions.

Develop, deploy, and maintain LLM pipelines and RAG QA/search systems; design and optimize prompts and multi-agent LLM architectures; operate multi‑GPU/cluster inference; build evaluation pipelines for model quality, bias, and hallucination; collaborate with product and CS teams to integrate conversational AI.

The Senior Data Engineer/Consultant will lead data engineering engagements, focusing on Databricks solutions, mentoring teams, and delivering high-quality data pipelines and integrations.

Senior hands-on consulting role to design, build and optimise Microsoft Fabric-based data platforms. Build Lakehouse/Warehouse solutions, develop ingestion and transformation pipelines with Python/PySpark/SQL, apply DevOps and data governance, work directly with clients, lead technical discussions, mentor engineers, and ensure production reliability and performance.