Top Data Engineer Jobs in Wellington

Build and maintain production data pipelines ingesting from SAP, POS, logistics and marketing systems. Migrate legacy pipelines to modern architectures, monitor and improve data quality, support platform infrastructure, collaborate cross-functionally, document processes, and apply automation and AI to improve workflows.

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.

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.

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.

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.

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