Top Data Engineer Jobs in Wellington

Leads the design, delivery, and evolution of enterprise data platforms, pipelines, and products. Provides hands-on technical leadership across squads and programs, supports analytics and AI initiatives, establishes engineering standards, and coaches data engineers. The role also oversees data governance, security, observability, automation, technical debt, and operational excellence while translating business requirements into scalable, reliable solutions.

Senior Data Engineer responsible for designing, provisioning, implementing, and supporting Azure data platforms. The role covers data warehousing, data lakes, analytics, database migration, Azure PaaS SQL environments, automation, monitoring, CI/CD, and DataOps. The engineer will gather business requirements, deliver data solutions using Azure services and Fabric, support data ingestion and cleansing, and assist internal and external engineering teams. This is a three-month extendable contract available anywhere in New Zealand.

Build and maintain batch and streaming data pipelines, Airflow workflows, data models, and warehouse datasets for a crypto trading platform. Improve data quality, freshness, performance, and cost efficiency through monitoring, validation, troubleshooting, and optimization. Collaborate with engineering and business users to define datasets, metrics, and documentation. This fully remote APAC role requires strong Python and SQL skills, hands-on Kafka, Spark, and Airflow experience, crypto or Web3 data engineering experience, and clear Mandarin communication.

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.

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.

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