At a Glance
- Tasks: Design and build scalable data pipelines for customer-focused projects.
- Company: Leading UK retail organisation with a focus on data and AI.
- Benefits: Hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a strong emphasis on innovation and problem-solving.
- Why this job: Join a dynamic team tackling exciting data challenges in retail and AI.
- Qualifications: Experience in data engineering, Python, SQL, and cloud platforms.
The predicted salary is between 63000 - 77000 £ per year.
We are seeking an experienced Senior Data Engineer to join the Customer Data team within the data and AI function of a leading UK retail organisation. The team is responsible for building and operating the data foundations that support a wide range of customer-focused use cases, including Customer 360, analytics, AI/ML, marketing and data-driven commercial initiatives. This is a hands-on engineering role for someone who enjoys solving complex data problems, building scalable solutions and working within modern software engineering environments. You will play a key role in designing and delivering reliable, production-grade data ingestion and transformation pipelines, while contributing to the wider architecture and technical direction of customer data capabilities. The successful candidate will be comfortable taking ownership of technical problems, developing solutions independently and working collaboratively with senior engineers and stakeholders to sense-check and evolve those solutions.
Key Responsibilities
- Design, build and operate scalable data ingestion and transformation pipelines for high-volume customer data.
- Develop robust, reliable and production-grade data solutions supporting Customer 360, analytics, AI/ML, marketing and commercial use cases.
- Contribute to solution design and technical architecture, taking a holistic view of systems, integrations, dependencies and potential risks.
- Build and maintain data pipelines with a strong focus on performance, reliability, scalability and data quality.
- Work across development and production environments, following established CI/CD, version control and release processes.
- Identify technical risks, integration points and opportunities for improvement across the wider data estate.
- Collaborate closely with Data Engineers, Software Engineers, Architects, Product and other technical teams to deliver complex data initiatives.
- Contribute to the design of real-time, high-throughput and low-latency data solutions where appropriate.
- Support the development of data capabilities used across customer, analytics, AI/ML and commercial data products.
- Produce clear technical documentation and contribute to maintaining a well-governed and supportable data environment.
- Proactively investigate and resolve complex technical and data engineering issues.
- Take ownership of engineering problems from initial solution through to deployment and ongoing operation.
About You
We are looking for a software-engineering-minded Data Engineer with strong foundations in data engineering and modern engineering practices. You should be someone who can take a problem, develop a pragmatic solution with relatively little oversight and then work with senior technical colleagues to sense-check and refine the approach. You will ideally have:
- Strong commercial experience as a Data Engineer, working on production-scale data platforms and pipelines.
- Strong software engineering fundamentals, ideally with a background in Computer Science, Software Engineering or a similar technical discipline.
- Proven experience designing and building data ingestion, transformation and integration pipelines at scale.
- Strong understanding of software engineering practices including Git/GitHub, CI/CD, development environments, testing and release management.
- Strong hands-on experience with Python and SQL.
- Experience working with modern cloud-based data platforms across AWS, Azure and/or GCP.
- Experience with contemporary data engineering technologies and architectures.
- Strong understanding of data modelling, distributed systems and scalable architecture patterns.
- A proactive approach to problem solving, with the ability to work independently and identify issues before they become blockers.
- Experience working in engineering teams where quality, maintainability, observability and production reliability are important.
- Strong communication skills and the ability to collaborate effectively with engineers, technical leads and wider stakeholders.
Technical Environment
Experience with some of the following technologies would be beneficial:
- Python
- SQL
- Cloud platforms – AWS, Azure or GCP
- Databricks
- Kafka / event-driven architectures
- Airflow
- dbt
- Git / GitHub
- CI/CD
- Infrastructure as Code
- Modern data platforms and distributed processing technologies
Experience with Databricks or Hadoop-style data processing environments is useful, although candidates with strong transferable experience across modern data platforms will be considered.
Customer Data & Retail Context
Experience within retail or e-commerce would be advantageous, particularly exposure to customer data environments, MarTech, CRM or digital customer journeys. Experience with any of the following would also be beneficial:
- Customer 360
- Customer Data Platforms
- Identity resolution
- Reverse ETL
- MarTech / CRM integrations
- Data monetisation
- High-throughput or low-latency data systems
- Customer data governance and privacy
These areas are not essential, provided you have strong core Data Engineering and software engineering experience.
Working Arrangement
The role is based in Waterloo, London, with hybrid working and occasional attendance at the office. The organisation is open to flexibility around the frequency of office attendance, although candidates based in the UK are strongly preferred due to collaboration, communication and occasional face-to-face requirements. This is an opportunity to join a well-established data engineering function working on large-scale customer data challenges across retail, analytics, AI/ML and commercial use cases.
Senior Data Engineer employer: Morson Talent
At TKMS ATLAS UK, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our Dorset location provides a unique opportunity for our Field Service Engineers to engage in meaningful projects with the Royal Navy and beyond, while enjoying comprehensive benefits and robust career development pathways. Join us to be part of a team that values your expertise and supports your professional growth through exciting global travel opportunities.
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We think this is how you could land Senior Data Engineer
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We think you need these skills to ace Senior Data Engineer
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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!
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✨Brush Up on Your Statistics
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✨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.
