Top Data Engineer Jobs in Wellington

Build, maintain, and improve SQL/Python data pipelines and analytical datasets. Collaborate with analytics, data science, product, and engineering teams to ensure data reliability, observability, testing, and documentation in a cloud-based environment.

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.

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.

Design, develop, and maintain high-performance, highly available backend services and APIs for Big Data products using Java/Python. Manage full service lifecycle, capacity planning, profiling/benchmarking, troubleshooting, security, and system architecture. Contribute to open-source big data projects and build scalable tools for global operations.

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

Lead design, development, deployment, and continuous improvement of cloud-native data and analytics solutions on Azure. Act as a hands-on technical lead building scalable, secure end-to-end data platforms using Spark/Databricks, Python/PySpark, and orchestration tools. Ensure CI/CD, DevOps, automation, code quality, mentor team members, resolve complex technical issues, and collaborate with stakeholders and vendors to drive platform evolution.

Build, deploy, and support cloud-native data and analytics solutions on Azure. Design and maintain data pipelines, ingestion, transformation and integration processes using Apache Airflow. Ensure data quality, monitoring, CI/CD and infrastructure-as-code. Troubleshoot platform issues, collaborate with cross-functional teams, and contribute to platform improvements and documentation.