At a Glance
- Tasks: Design and build modern data platforms and scalable ecosystems using cutting-edge technologies.
- Company: Global tech consultancy with a focus on impactful data engineering solutions.
- Benefits: Work on high-impact projects with autonomy and opportunities for growth.
- Other info: Collaborative environment with mentorship from senior engineers.
- Why this job: Join a team of experts and make a real difference in data engineering.
- Qualifications: Strong Python, SQL skills, and experience with Spark and cloud data services.
The predicted salary is between 63000 - 77000 £ per year.
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™.
Responsibilities:
- 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
- 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
- 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
- Process and transform large datasets using Spark and Flink
- Design systems that perform in production - not just on paper
- Work across relational, NoSQL, and analytical stores (Postgres, BigQuery, Snowflake, Cassandra, MongoDB)
- Optimise storage formats and access patterns (Parquet, Delta, ORC, Avro)
- Implement secure, compliant data solutions with security by design
- Embed governance without killing developer velocity
- 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
- 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
Requirements:
- Strong Python and SQL
- Deep experience with Spark and modern data platforms (Databricks / Snowflake)
- Solid grasp of cloud data services (AWS or GCP)
- 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
- Built and operated large-scale data pipelines in production
- Strong data modelling capability and architectural judgement
- Comfortable with multiple storage technologies and formats
- Infrastructure-as-code experience (Terraform, Pulumi)
- CI/CD pipelines using tools like GitHub Actions, ArgoCD
- Data testing and quality frameworks (dbt, Great Expectations, Soda)
- 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
Conditions:
- 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
Data engineer employer: Simple Machines
At Simple Machines, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to excel in their roles. As a Principal Software Engineer in London, you will benefit from a hybrid work model, competitive compensation, and opportunities for professional growth while working on cutting-edge technology projects that make a real impact for our clients. Join us to be part of a dynamic team where your contributions are valued and your career can flourish.
StudySmarter Expert Advice🤫
We think this is how you could land Data engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Simple Machines!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data engineer at Simple Machines.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Simple Machines.
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When you find a suitable opening like Data engineer at Simple Machines, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Simple Machines, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Simple Machines. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Simple Machines
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Simple Machines!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
