At a Glance
- Tasks: Lead the design and development of cutting-edge data platforms and pipelines.
- Company: Join Simple Machines, a global tech consultancy with a focus on impactful data solutions.
- Benefits: Enjoy autonomy, professional growth, and work on high-impact projects with senior engineers.
- Other info: Dynamic environment with opportunities to influence technical culture and mentor others.
- Why this job: Make a real difference by solving complex data challenges and shaping modern architectures.
- Qualifications: Strong Python and SQL skills, experience with Spark and cloud data services.
The predicted salary is between 80000 - 100000 £ per year.
Simple Machines is a global, independent technology consultancy operating across Sydney, New Zealand, London, Poland and San Francisco. 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.
This is a hands‑on principal 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. You’ll design and build greenfield data platforms, real‑time pipelines, and data products for clients who are serious about using data properly. You’ll work in small, high‑calibre teams and operate close to both the problem and the client.
If you enjoy solving hard data problems, shaping modern architectures (data mesh, data products, contracts), and delivering real outcomes — this is your lane.
What You’ll Be Doing
- 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, and 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, and GCP
- Apply modern architectural patterns: data mesh, data products, and data contracts
- Integrate deeply with client systems to enable scalable, consumer‑oriented data access
- Develop High‑Performance Pipelines
- Build and optimise batch and real‑time pipelines
- Work with streaming and event‑driven tech such as Kafka, Flink, Kinesis, Pub/Sub
- Orchestrate workflows using Airflow, Dataflow, Glue
- Work at Scale
- Process and transform large datasets using Spark and Flink
- Design systems that perform in production – not just on paper
- Own Data Storage & Performance
- Work across relational, NoSQL, and analytical stores (Postgres, BigQuery, Snowflake, Cassandra, MongoDB)
- Optimise storage formats and access patterns (Parquet, Delta, ORC, Avro)
- Cloud, Security & Governance
- Implement secure, compliant data solutions with security by design
- Embed governance without killing 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, providing clear technical direction and mentorship
- Raise the bar on data quality, testing, observability, and operational excellence
What We’re Looking For
- Core Engineering Strength
- Strong Python and SQL
- Deep experience with Spark and modern data platforms (Databricks / Snowflake)
- Solid grasp of cloud data services (AWS or GCP)
- Architecture & Design Judgement
- Demonstrated ownership of large‑scale data platform architectures
- Strong data modelling skills and architectural decision‑making ability
- Comfortable balancing trade‑offs between performance, cost, and 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 formats
- Engineering Discipline
- Infrastructure‑as‑code experience (Terraform, Pulumi)
- CI/CD pipelines using tools like GitHub Actions, ArgoCD
- Data testing and quality frameworks (dbt, Great Expectations, Soda)
- Delivery & Consulting Mindset
- Experience in consulting or professional services environments
- Strong consulting instincts — able to challenge assumptions and guide clients toward better outcomes
- Comfortable mentoring senior engineers and influencing technical culture
Why Simple Machines
- You’ll work on interesting, high‑impact problems
- You’ll build modern platforms, not maintain legacy mess
- You’ll be surrounded by senior engineers who actually know their craft
- You’ll have autonomy, influence, and room to grow
If you’re a senior data engineer who wants to build properly, think clearly, and deliver real outcomes - we should talk.
Principal Data Engineer employer: Internetwork Expert
At Simple Machines, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our teams are composed of high-calibre professionals who tackle meaningful challenges in data engineering, providing ample opportunities for personal and professional growth. With a focus on building modern data platforms in vibrant locations like Sydney, you will enjoy a dynamic work environment that values autonomy, creativity, and impactful contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that Principal Data Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving modern data platforms and real-time pipelines. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with cloud services like AWS or GCP, and how you've tackled complex data challenges in the past.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining Simple Machines. Tailor your application to highlight your experience with data mesh and architectural decision-making to stand out.
We think you need these skills to ace Principal Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Principal Data Engineer role. Highlight your experience with data platforms, cloud services, and any relevant projects you've led. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to show us your personality and passion for data engineering. Share specific examples of your work, especially those that demonstrate your problem-solving skills and technical leadership. Let us know why you're excited about joining Simple Machines!
Showcase Your Technical Skills:In your application, don't shy away from detailing your technical expertise. Mention your proficiency in Python, SQL, and any experience with tools like Databricks or Snowflake. We love seeing candidates who can clearly articulate their technical journey and achievements.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. This way, we can ensure your application gets the attention it deserves. Plus, it’s a great opportunity to explore more about us and what we do!
How to prepare for a job interview at Internetwork Expert
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, SQL, Spark, and cloud services such as AWS or GCP. Brush up on your knowledge of data platforms like Databricks and Snowflake, as you'll likely be asked to discuss your experience with these tools.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex data problems. Think about how you designed scalable data ecosystems or made architectural decisions that had a significant impact. This is your chance to demonstrate your hands-on experience and technical judgement.
✨Understand the Business Context
Familiarise yourself with how data engineering fits into broader business goals. Be ready to explain how your work can translate into real outcomes for clients. This will show that you’re not just a techie but also someone who understands the importance of data in driving business success.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s projects, team dynamics, and their approach to data governance and security. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals.
