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For Companies At a Glance
- Tasks: Design and build modern data platforms and real-time pipelines for impactful projects.
- Company: Join Simple Machines, a global tech consultancy with a focus on innovation.
- Benefits: Enjoy competitive salary, remote work options, and opportunities for professional growth.
- Why this job: Work on exciting data challenges and make a real difference in the tech world.
- Qualifications: Strong Python and SQL skills, experience with Spark and cloud data services.
- Other info: Collaborate with senior engineers in a dynamic, agile environment.
The predicted salary is between 48000 - 72000 ÂŁ per year.
Simple Machines is a global, independent technology consultancy operating across London, Poland, Sydney, San Francisco, and New Zealand. We design and build modern data platforms, intelligent systems, and bespoke software at the intersection of data engineering, AI, and software engineering. 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 senior engineering role, not an architecture‑only seat and not a support function. You will design and build greenfield data platforms, real‑time pipelines, and data products for clients who are serious about using data properly. You will 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 Will Be Doing
- 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
What We Are 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)
- 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)
- Nice to Have
- JVM or systems languages (Scala, Java, Go, Rust)
- Graph or specialised stores (Neo4j, Cassandra)
- Delivery & Consulting Mindset
- Experience in consulting or professional services environments
- Comfortable working in agile teams
- Able to engage stakeholders and drive outcomes, not just ship code
Benefits
- You will work on interesting, high‑impact problems
- You will build modern platforms, not maintain legacy mess
- You will be surrounded by senior engineers who actually know their craft
- You will have autonomy, influence, and room to grow
If you are a senior data engineer who wants to build properly, think clearly, and deliver real outcomes — we should talk.
Senior Data Platform Engineer - London employer: Simple Machines
Contact Detail:
Simple Machines Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Platform Engineer - London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects. When you apply through our website, include links to your work to stand out from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to data platforms. We want to see how you think and solve problems, so be ready to demonstrate your expertise!
✨Tip Number 4
Follow up after interviews! A quick thank-you email can keep you top of mind. Plus, it shows you’re genuinely interested in the role and the company.
We think you need these skills to ace Senior Data Platform Engineer - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Data Platform Engineer role. Highlight your hands-on experience with data platforms, cloud services, and any relevant projects you've worked on.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data engineering and how you can contribute to our mission at Simple Machines. Share specific examples of how you've solved complex data problems in the past.
Showcase Your Technical Skills: Don’t shy away from listing your technical proficiencies, especially in Python, SQL, and any cloud technologies like AWS or GCP. We want to see your expertise shine through in your application!
Apply Through Our Website: For the best chance of getting noticed, make sure to apply directly through our website. It helps us keep track of applications and ensures you’re considered for the role you’re excited about!
How to prepare for a job interview at Simple Machines
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Databricks, Snowflake, AWS, and GCP. Brush up on your Python and SQL skills, and be ready to discuss how you've used these tools in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of complex data problems you've solved. Think about how you designed and built data platforms or pipelines, and be ready to explain your thought process and the impact of your solutions.
✨Understand the Client's Needs
Since this role involves consulting directly with clients, demonstrate your ability to translate business needs into technical solutions. Research Simple Machines and their clients, and think about how you can add value to their projects.
✨Emphasise Collaboration and Agility
Highlight your experience working in agile teams and engaging stakeholders. Be prepared to discuss how you’ve driven outcomes beyond just coding, showcasing your delivery mindset and ability to work closely with others.
