How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior Data Engineer
Senior Data Engineer
About Simple Machines
Simple Machines is a global, independent technology consultancy operating across Sydney, New Zealand, London, and Poland. We design and build modern data platforms, intelligent systems, and bespoke software at the intersection of Data Engineering, Software Engineering and AI. We work with enterprises, scale-ups, and government to turn messy, high-value data into products, platforms, and decisions that actually move the needle. We don't do generic. We build things that matter—We engineer data to life™.
The Role
This is a hands-on senior engineering role, not an architecture-only seat and not a support function.
You'll be responsible for:
- Technical direction, platform design, and architectural decision-making
- Designing and building greenfield data platforms, real-time pipelines, and data products for clients serious about data usage
- Working in small, high-calibre teams, operating close to both the problem and the client
Responsibilities
Lead Platform & Architecture Design
- Own the end-to-end architecture of modern, cloud-native data platforms
- Design scalable data ecosystems using data mesh, data products, and data contracts
- Make high-impact architectural decisions across:
- Ingestion
- Storage
- Processing
- Access layers
- Ensure platforms are secure, compliant, and production-grade by design
Build Modern Data Platforms
- Design and deliver cloud-native data platforms using:
- Databricks
- Snowflake
- AWS
- GepCloud
- Apply modern architectural patterns: data mesh, data products, and data contracts
- Integrate deeply with client systems to enable scalable, consumer-oriented data access
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Develop High-Performance Pipelines
- Build and optimise batch and real-time pipelines
- Work with streaming and event-driven tech:
- Kafka
- Flink
- Kinesis
- Pub/Sub
- Orchestrate workflows using:
- Apache Airflow
- Dataflow
- Glue
Work at Scale
- Process and transform large datasets using:
- Spark
- Flink
- Design production-performant systems – not just theoretical or academic designs
Own Data Storage & Performance
- Work across:
- Relational stores (Postgres)
- NoSQL stores (Cassandra, MongoDB)
- Analytical stores (BigQuery, Snowflake)
- Optimise:
- Storage formats (Parquet, Delta, ORC, Avro)
- Access patterns
Cloud, Security & Governance
- Implement secure, compliant data solutions with security by design
- Embed governance without compromising developer velocity
Consult and Influence
- Work directly with clients to understand problems and shape solutions
- Translate business needs into pragmatic engineering decisions
- Act as a trusted technical advisor – not just an order-taker
Technical Leadership & Quality
- Set engineering standards, patterns, and best practices across teams
- Review designs and code to provide clear technical direction and mentorship
- Raise the bar on:
- Data quality
- Testing
- Observability
- Operational excellence
Requirements
Core Engineering Strength
- Strong proficiency in Python and SQL
- Deep experience with Spark and modern data platforms (including Databricks and Snowflake)
- Solid grasp of cloud data services (AWS or Google Cloud Platform)
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Architecture & Design Judgement
- Demonstratable ownership of large-scale data platform architectures
- Strong data modelling skills and architectural decision-making ability
- Comfortable balancing trade-offs between:
- Performance
- Cost
- Complexity
Data Platform Experience
- Built and operated large-scale data pipelines in production
- Strong data modelling capability and architectural judgement
- Comfortable with multiple storage technologies and file formats
Engineering Discipline
- Experience with infrastructure-as-code (IaC) (e.g., Terraform, Pulumi)
- CI/CD pipeline expertise using tools like:
- GitHub Actions
- ArgoCD
- Applied data testing and quality frameworks:
- dbt
- Great Expectations
- Soda
Delivery & Consulting Mindset
- Experience in consulting or professional services environments
- Strong consulting instincts:
- Ability to challenge assumptions
- Capacity to guide clients toward better outcomes
- Comfortable mentoring senior engineers and influencing technical culture
Benefits
Why Simple Machines?
You’ll:
- Work on interesting, high-impact problems
- Build modern platforms, not maintain legacy systems
- Collocate with Kubernetes for data platforms / modern data engineering startups (assuming was part of culture)
- Have autonomy, influence, and growth opportunities
- Be part of a team of trusted architects and engineers who think clearly and deliver real outcomes
If you're a Senior Data Engineer who:
- Wants to build properly
- Prefers clear thinking
- Enjoys delivering real outcomes
—we should talk.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location