Data Platform Engineer

Vector Limited

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profile Job Location:

Auckland - New Zealand

profile Monthly Salary: Not Disclosed
Posted on: 9 hours ago
Vacancies: 1 Vacancy

Job Summary

Role: Data Platform Engineer

Number of positions: 1

Type: Permanent Full Time

Location: Auckland

Hours: Guarantee of 40 hours per week between the hours of 8am and 5pm Monday to Friday.

Salary: $108000 - $125000

 

At Vector were not just upgrading infrastructure - were transforming how energy is delivered and experienced. Backed by a $4.6 billion investment over the next decade were modernising our electricity distribution network and embedding smart digital technologies across everything we do. This is the heart of our Symphony Strategy: a bold move toward a cleaner more resilient and more responsive energy future.

But this transformation goes far beyond the grid. As a technology-enabled organisation data is at the core of our evolution. Were building intelligent platforms and products that turn information into actionenabling better decisions unlocking innovation and delivering real value to customers and communities. To support this vision were seeking a talented Data Platform Engineer to join our high-performing team.

The Role:

The Data Platform Engineer is responsible for the build management maintenance and optimisation of Vectors hybrid data platform ecosystem - spanning the modern cloud stack (Snowflake AWS Coalesce Fivetran) and the on-premise SQL environments that remain in operation. This role ensures the platform is performant secure and continuously improving through proactive monitoring automation and optimisation. The Data Platform Engineer contributes directly to Vectors ability to deliver trusted timely and scalable data by applying engineering best practice across all environments.

What Youll Be Doing:

  • Design build and optimise the data platform by configuring and enhancing Snowflake environments supporting AWS infrastructure tuning compute performance and optimising storage/compute utilisation.
  • Develop maintain and improve data pipelines using Fivetran Coalesce or similar tools while supporting schema design data modelling and ensuring reliable connectivity between onpremise SQL databases and the cloud platform.
  • Oversee platform operations and reliability including monitoring system health and job performance responding to incidents performing patching and upgrades and managing backup recovery and disasterrecovery processes across cloud and onprem systems.
  • Apply DevOps/DataOps practices by implementing CI/CD pipelines InfrastructureasCode templates Gitbased workflows and automation to reduce manual effort increase speed and lower operational costs.
  • Collaborate with squads and analysts to troubleshoot issues quickly while also supporting governance teams with metadata lineage and dataquality visibility.
  • Manage platform security and compliance ensuring access controls encryption logging monitoring and audit trails are consistently applied.
  • Document procedures configurations and runbooks to ensure repeatability operational consistency and audit readiness.

About You:

Youre an experienced engineer with:

  • A relevant bachelor degree or higher in the areas of electronics engineering computer or information sciences and 12 months of experience as a Platform Engineer or Data Engineer with a strong foundation in designing and implementing scalable data solutions.
  • If qualification cannot be met 5 years of experience as a Platform Engineer or Data Engineer with a strong foundation in designing and implementing scalable data solution is required.
  • Good understanding of Electricity Distribution Business Network reliability metrics and Regulatory reporting.
  • Hands-on experience with Snowflake Fivetran Coalesce Power BI Reporting AWS services (S3 Lambda EC2 CloudWatch) and SQL Server/Oracle.
  • Proficiency in Python SQL and scripting for automation.
  • Familiarity with CI/CD Infrastructure-as-Code (Terraform CloudFormation) and version control (Git).
  • Experience in managing day to day activities of DataOps DevOps and modern data platform.
  • Strong problem-solving and analytical skills; comfortable troubleshooting complex environments.
  • Detail-oriented collaborative and passionate about performance optimisation and automation.

Why Join Vector

  • Competitive salary between $108000 - $125000
  • Be part of a transformative forward-thinking organisation at the forefront of energy and digital innovation
  • Work in a collaborative and inclusive environment with a strong focus on professional development
  • Enjoy flexibility including work-from-home options and flexible hours
  • Comprehensive health and wellbeing support
  • Great benefits that reflect the importance of family

Ready to shape the future of energy through data Apply now! This job advert will close on the 4th of February and applications will be reviewed as they are received.

Vector is proud to be:

First corporate Living Wage Accredited employer

First Accessibility Tick employer

Rainbow Tick accredited

We value diversity and welcome applications from candidates of all backgrounds. If you require assistance during the application process please contact us at.

 


Additional Information :

We know that some people may hesitate to apply if they dont meet every single requirement. If this role excites you we encourage you to apply anyway - your skills enthusiasm and unique perspective could be just what were looking for.

Vector values diversity in all its forms and welcomes people of all backgrounds experiences identities and abilities to be part of our team.


Remote Work :

No


Employment Type :

Full-time

Role: Data Platform EngineerNumber of positions: 1Type: Permanent Full TimeLocation: AucklandHours: Guarantee of 40 hours per week between the hours of 8am and 5pm Monday to Friday.Salary: $108000 - $125000 At Vector were not just upgrading infrastructure - were transforming how energy is delivered ...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala