Senior Data Engineer
Simple Machines7 months ago
Christchurch, New ZealandSenior
Responsibilities
- Design and build client-specific data platforms, pipelines, and integrations.
- Develop batch and real-time data processing solutions at scale.
- Work directly with clients to understand requirements, shape expectations, and advise on data architecture and engineering best practices.
- Learn and adapt to new cloud platforms, tools, and frameworks as project needs evolve.
- Share knowledge with client teams and establish effective engineering practices.
- Contribute to security, governance, and quality across delivered solutions.
Requirements
- At least 5 years of professional experience in data engineering, software engineering, or a closely related field.
- Strong data or software engineering fundamentals and the ability to write clean, well-tested, production-quality code.
- Proficiency in multiple programming languages, ideally including Python.
- Experience with AWS, GCP, and/or Azure and cloud-native services.
- Strong experience with SQL, databases and/or data warehouses, data modeling, and data storage patterns.
- Exposure to containerization, CI/CD, and infrastructure-as-code concepts.
- Strong communication skills for translating technical concepts to non-technical stakeholders and understanding client needs.
- A curious, adaptable mindset and willingness to learn new technologies.
- A degree or equivalent experience in computer science or a related field.
- Consulting or professional services experience is beneficial but not required.
Benefits
- Hybrid workplace arrangement.
- Full-time role based in Christchurch, New Zealand.
- Opportunity to work on greenfield data solutions and varied client projects across data engineering, software engineering, and AI.
Tech Stack
Categories
Data Engineering
About Simple Machines
Simple Machines is a privately held consulting and engineering firm that designs and builds data platforms, machine-learning/AI systems, and bespoke software for enterprises and public-sector clients. The company provides architecture, data engineering, and scalable distributed systems expertise across AWS, GCP, Azure, Databricks, Snowflake, and Confluent. Founded in 2008 and headquartered in Sydney, it operates globally with teams in Australia, the UK, Europe, and New Zealand.