Data Engineer: Azure, Databricks & ETL Solutions

Qjumpers

Wellington

On-site

NZD 120,000 - 150,000

Full time

2 days ago
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Job summary

Qjumpers in Wellington is seeking a Data Engineer to join our data engineering team, designing, building, and supporting data solutions that enable reliable analytics and reporting while improving data quality, consistency and security. You will solve complex data problems and have an engineering mindset, focusing on data quality, security, automation and continuous improvement.

The role involves ETL pipelines, data stores, data warehouses and data marts, with collaboration across the Data

Qualifications

  • 5+ years' experience in software development (Python)
  • 3 years’ experience in Databricks
  • Advanced SQL knowledge and database technologies
  • Experience in cloud platforms, preferably Microsoft Azure
  • Experience with ETL or data flow management tools
  • DevOps experience is beneficial

Responsibilities

  • Design and build complex data solutions including ETL pipelines, data stores, data warehouses and data marts.
  • Support data modelling to ensure consistent data definitions.
  • Collaborate with Data Platform team to improve standards and best practices.
  • Improve data access controls, coding practices, deployment approaches and automated testing.
  • Monitor and maintain data platforms, environments and data loads for reliability.
  • Investigate incidents and resolve technical issues with Technology Services.
  • Contribute to technical planning and ongoing improvement of the bank's technology services.

Skills

Python
Databricks
Advanced SQL
Azure
ETL
DevOps

Job description

Qjumpers in Wellington is seeking a Data Engineer to join our data engineering team, designing, building, and supporting data solutions that enable reliable analytics and reporting while improving data quality, consistency and security. You will solve complex data problems and have an engineering mindset, focusing on data quality, security, automation and continuous improvement.

The role involves ETL pipelines, data stores, data warehouses and data marts, with collaboration across the Data

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