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- Tasks: Design and build modern data platforms and real-time pipelines for impactful clients.
- Company: Join Simple Machines, a global tech consultancy with a focus on innovation.
- Benefits: Enjoy autonomy, competitive salary, and opportunities for professional growth.
- Why this job: Tackle exciting data challenges and make a real difference in the tech world.
- Qualifications: Strong Python, SQL, and experience with data platforms like Databricks and Snowflake.
- Other info: Collaborate with senior engineers in a dynamic, agile environment.
The predicted salary is between 36000 - 60000 £ 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’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
- 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’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)
- 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’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.
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 the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data platforms and pipelines. This gives you a chance to demonstrate your expertise and makes you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data engineering. Practice common interview questions and be ready to discuss how you've tackled real-world data challenges.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Simple Machines.
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 specific 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 your background makes you a great fit for our team. 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 services like AWS or GCP. We want to see your expertise in action, so include any relevant projects or achievements.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen to join our team!
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 Python, SQL, and cloud services such as AWS or GCP. Brush up on your experience with data platforms like Databricks and Snowflake, as well as your knowledge of Spark. Being able to discuss these tools confidently will show that you're ready for the hands-on nature of the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex data problems. Think about how you’ve designed and built data platforms or optimised pipelines in the past. This is your chance to demonstrate your engineering discipline and architectural judgement, so have those stories ready to share!
✨Understand the Client's Perspective
Since this role involves consulting directly with clients, it’s crucial to show that you can translate business needs into technical solutions. Research Simple Machines and their clients beforehand, and be prepared to discuss how you would approach understanding and solving their unique challenges.
✨Emphasise Collaboration and Agility
Highlight your experience working in agile teams and your ability to engage stakeholders effectively. Discuss how you’ve collaborated with others to drive outcomes, not just ship code. This will resonate well with the company culture at Simple Machines, which values teamwork and influence.
