Azure Snowflake Engineer

InfoCentric

1d

About The Position

As an Azure Snowflake Data Engineer, you will play a key role in designing and delivering modern data platforms for our clients. This is a client-facing role suited to someone who thrives in consulting environments and enjoys solving complex business and technical challenges. Key Responsibilities Design and deliver scalable, secure, and cost-effective data platforms on Microsoft Azure Build and orchestrate robust data pipelines using Azure Data Factory (ADF) Develop, optimise, and manage enterprise-grade data models in Snowflake Implement transformation and analytics engineering frameworks using dbt Lead or contribute to large-scale data transformation programs Work closely with client stakeholders to gather requirements and translate business needs into technical solutions Establish best practices across data architecture, modelling, governance, and CI/CD Optimise performance, reliability, and cost in cloud environments Required Experience & Skills 5+ years’ experience in data engineering, ideally within consulting or professional services Demonstrated experience delivering large-scale enterprise data projects (multi-source integrations, high-volume datasets, complex transformations) Strong hands-on expertise in: Microsoft Azure data services (Data Lake, Synapse, Azure SQL, etc.) Azure Data Factory (ADF) Snowflake dbt Advanced SQL and strong data modelling skills (dimensional modelling, ELT patterns) Experience designing cloud-native architectures Strong understanding of DevOps, CI/CD, and infrastructure-as-code principles Experience implementing data quality, lineage, and governance frameworks Excellent stakeholder communication skills Highly Regarded Experience in Australian enterprise environments (banking & finance, retail, government) Microsoft Azure or Snowflake certifications Experience with Agile delivery methodologies Experience contributing to solution architecture and technical design documentation What We’re Looking For A consulting mindset with strong client engagement capability Proven ability to deliver in complex, multi-stakeholder environments Strong ownership and accountability across the full delivery lifecycle Ability to balance technical excellence with pragmatic business outcomes Passion for mentoring and uplifting engineering capability

Requirements

• 5+ years’ experience in data engineering, ideally within consulting or professional services
• Demonstrated experience delivering large-scale enterprise data projects (multi-source integrations, high-volume datasets, complex transformations)
• Strong hands-on expertise in: Microsoft Azure data services (Data Lake, Synapse, Azure SQL, etc.)
• Azure Data Factory (ADF)
• Snowflake
• dbt
• Advanced SQL and strong data modelling skills (dimensional modelling, ELT patterns)
• Experience designing cloud-native architectures
• Strong understanding of DevOps, CI/CD, and infrastructure-as-code principles
• Experience implementing data quality, lineage, and governance frameworks
• Excellent stakeholder communication skills
• A consulting mindset with strong client engagement capability
• Proven ability to deliver in complex, multi-stakeholder environments
• Strong ownership and accountability across the full delivery lifecycle
• Ability to balance technical excellence with pragmatic business outcomes
• Passion for mentoring and uplifting engineering capability

Nice To Haves

• Experience in Australian enterprise environments (banking & finance, retail, government)
• Microsoft Azure or Snowflake certifications
• Experience with Agile delivery methodologies
• Experience contributing to solution architecture and technical design documentation

Responsibilities

• Design and deliver scalable, secure, and cost-effective data platforms on Microsoft Azure
• Build and orchestrate robust data pipelines using Azure Data Factory (ADF)
• Develop, optimise, and manage enterprise-grade data models in Snowflake
• Implement transformation and analytics engineering frameworks using dbt
• Lead or contribute to large-scale data transformation programs
• Work closely with client stakeholders to gather requirements and translate business needs into technical solutions
• Establish best practices across data architecture, modelling, governance, and CI/CD
• Optimise performance, reliability, and cost in cloud environments

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed