At a Glance
- Tasks: Design and maintain scalable data pipelines using cutting-edge technologies like Apache Spark and Databricks.
- Company: Join Totalmobile, a collaborative tech company that values diversity and innovation.
- Benefits: Enjoy a competitive salary, great benefits, and the chance to shape our data platform.
- Other info: Be part of an inclusive culture that celebrates diverse backgrounds and perspectives.
- Why this job: Make a real impact in a hands-on role with high ownership and autonomy.
- Qualifications: Experience in data engineering, strong Python skills, and familiarity with cloud technologies.
The predicted salary is between 50000 - 65000 £ per year.
We are looking for a versatile and pragmatic Platform Data Engineer to join our team. This is a hands-on role suited to someone who thrives across the full data stack, from ingestion and transformation through to serving reliable, well-structured data to consumers. You will be comfortable working across a range of technologies and environments, bringing both engineering rigour and a data-first mindset to everything you build. You will work closely with data architects, analysts, and product teams to design and deliver scalable data pipelines, implement robust storage patterns, and help shape our data platform strategy, primarily on Azure, with exposure to wider cloud environments.
Key Technologies
- Python
- Azure
- Databricks
- Apache Spark
- Delta Tables
- Parquet
- Unity Catalogue
Desirable
- C#
- DuckDB
- AWS
Key Responsibilities
- Design, build, and maintain scalable data pipelines using Apache Spark and Databricks, with a focus on reliability and performance.
- Work with structured and semi-structured data in Parquet and Delta Table formats, applying appropriate partitioning and optimisation strategies.
- Manage and evolve data assets within the Unity Catalogue, maintaining clear governance, lineage, and access controls.
- Collaborate with architects and engineers to define and uphold data modelling and ingestion best practices.
- Write clean, well-tested Python code; this is a core requirement of the role.
- Troubleshoot and resolve data quality, pipeline, and performance issues across the data platform.
- Contribute to infrastructure-as-code, CI/CD, and DevOps practices within an Azure-first environment.
- Support the wider engineering team as needed; this role requires genuine flexibility across the stack.
Required Skills & Experience
- Data Engineering: Solid, demonstrable experience in data engineering: pipeline design, data modelling, and working at scale.
- Strong understanding of columnar storage formats, particularly Parquet, and experience with Delta Lake / Delta Tables.
- Hands-on experience with Apache Spark, including DataFrame APIs, optimisation, and debugging.
- Experience with Databricks, including notebook development, job orchestration, and cluster management.
- Familiarity with Unity Catalogue or similar data governance and cataloguing tooling.
Programming
- Highly proficient in Python (non-negotiable). You should be comfortable with idiomatic Python, testing, packaging, and working in collaborative codebases.
- Comfortable reading and working across multiple technology stacks; you do not need to be an expert in everything, but you should be adaptable.
Cloud & Infrastructure
- Practical Azure experience, ideally including Azure Data Factory, Azure Data Lake Storage, Synapse Analytics, or similar services.
- Understanding of cloud-native design principles: scalability, cost-awareness, and security.
Engineering Practices
- Experience working in Agile teams with version control (Git), code review, and CI/CD pipelines.
- Good written and verbal communication, with the ability to articulate technical decisions to both technical and non-technical stakeholders.
Nice to Have
- Experience with C# or .NET, useful for integrations with existing backend services.
- Familiarity with DuckDB for lightweight, local analytical workloads or prototyping.
- AWS experience, useful for cross-cloud projects and broadening platform perspective.
- Experience with streaming data platforms such as Apache Kafka or Azure Event Hubs.
- Exposure to dbt, Great Expectations, or similar data transformation and quality tooling.
What We Offer
- A collaborative, engineering-led culture with high ownership and autonomy.
- Opportunity to help shape the data platform from the ground up.
- Competitive salary and benefits package.
Here at Totalmobile, we want our employees to feel valued, appreciated, and free to be who they are at work. We are committed to an inclusive workforce that fully represents many different cultures, backgrounds and viewpoints. We are dedicated to supporting inclusion and diversity at Totalmobile. We actively celebrate colleagues’ different abilities, sexual orientation, ethnicity, faith, and gender. Everyone is welcome and supported in their development at all stages in their journey with us.
Platform Data Engineer employer: TotalMobile
At Totalmobile, we pride ourselves on fostering a collaborative and engineering-led culture that empowers our employees to take ownership of their work. As a Platform Data Engineer, you will have the unique opportunity to shape our data platform from the ground up while enjoying a competitive salary and benefits package. We are committed to creating an inclusive environment where diverse perspectives are celebrated, ensuring that every team member feels valued and supported in their professional growth.
StudySmarter Expert Advice🤫
We think this is how you could land Platform Data Engineer
✨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 data engineering projects, especially those involving Python, Apache Spark, and Azure. This gives you a chance to demonstrate your hands-on experience and problem-solving abilities.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with data pipelines, governance, and collaboration with teams. Practice common interview questions to boost your confidence.
✨Tip Number 4
Don't forget to 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 awesome team at Totalmobile.
We think you need these skills to ace Platform Data Engineer
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with the key technologies mentioned in the job description. We want to see how your skills align with our needs, so don’t hold back on showcasing your data engineering prowess!
Show Off Your Python Skills:Since being proficient in Python is non-negotiable for this role, include specific examples of projects where you've used Python effectively. We love seeing clean, well-tested code, so if you have any GitHub repos or similar, share them with us!
Demonstrate Your Data Mindset:In your application, emphasise your data-first mindset and how you've applied it in past roles. We’re looking for someone who not only understands data but also knows how to manage and evolve it effectively, so let that shine through!
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 gives you a chance to explore more about our culture and values!
How to prepare for a job interview at TotalMobile
✨Know Your Tech Stack
Make sure you’re well-versed in the key technologies mentioned in the job description, especially Python, Apache Spark, and Azure Databricks. Brush up on your knowledge of Parquet and Delta Tables, as well as any experience you have with Unity Catalogue. Being able to discuss these technologies confidently will show that you're ready for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've designed and maintained data pipelines or resolved data quality issues. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help you demonstrate your hands-on experience and engineering rigour effectively.
✨Understand Agile Practices
Since the role involves working in Agile teams, be ready to talk about your experience with version control, code reviews, and CI/CD pipelines. Highlight how you’ve collaborated with others in a team setting and how you adapt to changing requirements, as this is crucial for success in a dynamic environment.
✨Communicate Clearly
Practice articulating your technical decisions in a way that both technical and non-technical stakeholders can understand. Good communication is key, so consider preparing a few examples where you’ve had to explain complex concepts simply. This will show that you can bridge the gap between different teams effectively.
