At a Glance
- Tasks: Design and build scalable data pipelines using Python, SQL, and Spark.
- Company: Join a fast-growing tech start-up with a culture of innovation.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Collaborative environment with exciting challenges and career advancement.
- Why this job: Make a real impact with cutting-edge AI technologies from day one.
- Qualifications: Strong coding skills in Python and SQL, plus experience with AWS and Spark.
The predicted salary is between 60000 - 75000 £ per year.
Salary: 60,000-75,000 Dependent on Experience
London: Hybrid working - 3 days per week in the office, 2 days home-based
Job Ref: J13171
Join a fast-growing technology start-up where you'll have the freedom to experiment with cutting-edge data and AI technologies, solve interesting problems and make a visible impact from day one.
Working alongside a talented team of engineers, analysts and data scientists, you won't be confined to one small part of the platform. You'll build scalable pipelines, work with large volumes of consumer data and explore new ideas at a pace that is often difficult to achieve within a larger organisation.
You'll bring strong Python, SQL and Spark fundamentals, along with genuine enthusiasm for how AI is transforming data engineering. You'll already be using AI-assisted development tools such as Claude, while having the technical ability to understand, review and challenge the code they produce.
Key Responsibilities
- Design, build and optimise scalable data pipelines and ETL/ELT processes.
- Develop and maintain data engineering solutions using Python, SQL and Spark.
- Work with large and complex datasets, ensuring data quality, reliability and performance.
- Use AI-assisted development tools to support coding, problem solving and delivery.
- Collaborate with engineering, analytics and data science teams to develop effective data solutions.
- Identify opportunities to automate processes and improve the scalability and efficiency of data workflows.
Essential Skills and Experience
- Strong hands-on data engineering experience.
- Strong coding fundamentals across Python and SQL.
- Hands-on experience working with Spark for large-scale data processing.
- Hands-on experience working with AWS data services.
- Experience designing and developing scalable data pipelines and ETL/ELT processes.
- Practical experience using AI-assisted development tools such as Claude within your day-to-day work.
- Strong communication skills and the ability to work effectively within a fast-moving, collaborative environment.
If you're a Data Engineer with strong technical fundamentals who wants the freedom to innovate, explore how AI is changing engineering and help shape a data platform as the business scales, we want to hear from you. Apply today!
Please note we can only accept applications from those with current UK working rights for this role. This client cannot offer visa sponsorship.
Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme.
Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website: www.datatech.org.uk
Data Engineer – AWS, Spark & AI employer: Datatech Analytics
Datatech Analytics is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration within the secure government and defence sectors. Employees benefit from meaningful projects that have a direct impact on national security, alongside opportunities for professional growth and development in cutting-edge technologies. With a hybrid working model and a focus on employee well-being, this role provides a unique chance to contribute to critical transformation programmes while enjoying a supportive and engaging workplace.
