Data Engineer

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Cloudwerx is a modern Salesforce, Snowflake & AI consultancy founded in 2018 to do things differently. We design and deliver clever, scalable, and human-centred data and cloud solutions that create real impact for our clients across public sector, education, health, financial services, utilities, and more.

From data modernisation on Snowflake and Databricks to analytics, AI, and Salesforce Data Cloud enablement - we help organisations turn data into trusted, actionable insight.

You’ll join our Data & AI practice, working closely with the Head of Data & AI, data engineers, analytics specialists, architects, and client stakeholders.

This is a close-knit squad of great minds - collaborative, curious, and deeply invested in solving complex data challenges together. The team values open thinking, shared ownership, and learning from one another, while delivering high-quality outcomes for clients.

As a Data Engineer, you’ll work shoulder-to-shoulder with experts across data engineering, analytics, and AI, contributing hands‑on while continuously growing your technical and consulting capability.

We’re looking for multiple Data Engineers with strong experience in cloud-based data engineering and modern data stacks. You’ll design and implement scalable, secure, and high-performing data solutions using technologies such as Snowflake, DBT/Coalesce, Fivetran, Databricks, and Python/Java, while also building capability in Salesforce CRMA and Data Cloud.

This is a consulting role - you’ll work across multiple client engagements, collaborate closely with cross‑functional teams, and provide guidance on best practices in data architecture, performance, governance, and cost optimisation.

• Design, build, and optimise modern data stack solutions using Snowflake, Databricks, DBT/Coalesce, and Fivetran
• Implement and maintain reliable ETL/ELT pipelines for efficient data ingestion, transformation, and governance
• Develop scalable data models and transformations to support analytics, reporting, and AI use cases
• Design cloud‑based data architectures across AWS, GCP, or Azure
• Optimise performance, security, data quality, and cost efficiency across data platforms
• Apply best practices for data governance, access control, and reliability

• Work directly with clients to understand requirements and translate them into scalable data solutions
• Provide strategic recommendations on modern data architecture and tooling
• Manage workloads across multiple client projects, ensuring timely delivery and quality outcomes

• Collaborate with data engineers, BI specialists, analysts, and architects to deliver end‑to‑end solutions
• Troubleshoot and resolve complex technical challenges across data pipelines and platforms
• Continuously improve delivery patterns, tooling, and engineering standards

• 3+ years’ experience designing and implementing modern data stacks
• Strong expertise in cloud-based databases, including performance tuning, optimisation, and security
• Experience with ELT tools such as Fivetran, DBT, or Coalesce
• Proficiency in Python or Java for data engineering, scripting, and automation
• Strong SQL and data modelling capability
• Experience working with cloud platforms (AWS, GCP, or Azure)
• Consulting or client‑facing experience, with strong communication and stakeholder management skills
• Proven ability to manage multiple projects and priorities in a fast‑paced environment
• Strong problem‑solving mindset and collaborative approach
• Work on cutting‑edge data and AI projects using modern cloud technologies
• Learn and grow across Snowflake, Databricks, Salesforce Data Cloud, and AI‑driven analytics
• Collaborative, supportive team culture with mentoring and knowledge sharing
• Flexible working arrangements - remote and hybrid options across ANZ
• Clear pathways for technical and consulting career progression

Seniority level

• Mid‑Senior level

Employment type

• Full‑time

Job function

• Information Technology

Industries

• IT Services and IT Consulting
• Data Infrastructure and Analytics

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