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Salary: 145000 Data Engineer / Permanent / Auckland / $150k NZD About the Company Our client is a Private Equity backed healthcare services organisation operating across Australasia. They're mid transformation,…
Build and maintain scalable data pipelines and GenAI platforms on AWS using Spark, Iceberg, and Bedrock to power analytics, AI, and RAG systems.
Build and maintain Snowflake-based data pipelines and AI platforms for clients, using Python, Spark, Airflow and Kubernetes to turn raw data into business insights.
Designs and maintains scalable data pipelines using PySpark and Delta Lake on Databricks to enable reliable data enrichment across platforms.
Designs and optimizes cloud-based data pipelines using AWS, PySpark, and Databricks to process and govern enterprise data in agile, international projects.
Build and optimize modern data platforms using Snowflake and Databricks, design scalable pipelines, and implement CRM/CDP solutions for large retail, banking, and automotive clients.
Build and optimize modern data pipelines and platforms using Snowflake and Databricks, then activate customer data in CRM/CDP systems like Salesforce and Adobe for marketing use cases.
Data Engineer building PySpark pipelines and Dataiku workflows to ingest, transform, and expose financial data for a large client, using cloud-based data lakes and CI/CD.
Design and maintain scalable data pipelines using Python, PySpark, and Spark Streaming to process batch and real-time data for high-quality datasets.
Build and maintain data pipelines in Azure Databricks (PySpark/SQL) and create Power BI dashboards to support project management and decision-making at a climate-tech company.
Build and maintain data pipelines in Python and Databricks, ensuring reliable, high-performance data processing and transformation for clients.
Build and deploy data pipelines, cloud data platforms, and ML systems for clients using Databricks, Spark, AWS, and MLOps tooling.
Design and optimize Spark-based AI training pipelines using Scala, PySpark, and Spark SQL for scalable data processing and efficient joins.
Build and maintain data pipelines in Azure Databricks with PySpark/SQL, then create and deliver Power BI dashboards to help teams make data-driven decisions.
Build and maintain a modern AWS-based data lakehouse and ETL pipelines for a large bank using PySpark, Java, and cloud-native tooling.
Build and maintain scalable data pipelines on Azure and Microsoft Fabric, from ingestion to analytics, using Azure Data Factory, Synapse, and Fabric components.
Senior Data Engineer role using Dataiku to design data pipelines, build visualizations, and advise clients on AI/ML solutions with Python, Spark, and cloud platforms.
Build and optimize data pipelines, analyze business needs, and deliver visualizations using Dataiku, Python, and Spark to drive AI-driven solutions for clients in finance, healthcare, mobility, and climate sectors.
Builds and maintains Snowflake-based data pipelines for banking clients, ensuring data quality and reliability using Python, PySpark, SQL and CI/CD.
Designs and maintains scalable GCP data pipelines (BigQuery, Dataflow, Dataproc) for retail clients, automating data flows and optimizing analytics infrastructure.
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