Cloud Data Engineer: Performance & Scale in Azure

Plan Partners

City of Melbourne

On-site

AUD 140,000 - 180,000

Full time

9 days ago
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Benefits offered by this job

12 weeks parental leave
Novated leasing benefits
Learning and development opportunities
Sonder wellbeing platform

Job summary

McMillan Shakespeare is seeking an experienced Cloud Data Specialist to own performance, data integrity, and scalability across enterprise systems. This hands-on role targets a seasoned DBA/Performance Engineer who will optimise SQL Server and Azure data services, design scalable data models, and support high-volume production environments.

The successful candidate will collaborate with architects, developers and data engineers to ensure secure, resilient data environments and will apply best

Qualifications

  • 5+ years DBA experience in a corporate complex business.
  • Deep expertise in SQL Server & Azure data services.
  • Proven experience in high-volume, production systems.
  • Strong understanding of database performance engineering.
  • Experience with query tuning and indexing is required.

Responsibilities

  • Own performance, stability, and availability of enterprise databases
  • Lead query optimisation, indexing, and performance tuning
  • Design and optimise data models (normalisation, schema design)
  • Support high-volume production systems (incidents, RCA, optimisation)
  • Embed best practices across DevOps and engineering teams

Skills

DBA experience
SQL Server
Azure data services
Query tuning
Data modelling
Performance engineering

Job description

McMillan Shakespeare is seeking an experienced Cloud Data Specialist to own performance, data integrity, and scalability across enterprise systems. This hands-on role targets a seasoned DBA/Performance Engineer who will optimise SQL Server and Azure data services, design scalable data models, and support high-volume production environments.

The successful candidate will collaborate with architects, developers and data engineers to ensure secure, resilient data environments and will apply best

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