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For Companies At a Glance
- Tasks: Build and optimise scalable data pipelines for a cutting-edge cloud-based platform.
- Company: Fast-growing B2B SaaS organisation focused on marketing data integrity.
- Benefits: Up to £80,000 salary, flexible working, 25 days holiday plus birthday off.
- Other info: Great opportunity for career growth in a supportive environment.
- Why this job: Join a dynamic team and make an impact in the world of data engineering.
- Qualifications: Experience in data engineering, strong SQL and Python skills required.
The predicted salary is between 80000 - 80000 £ per year.
About the Role
I am seeking a technically strong Data Engineer to support the development and scaling of a modern cloud‑based data platform within a fast‑growing B2B SaaS organisation that specialises in marketing data integrity. The company provides a platform that helps organisations automate and standardise the flow of lead and marketing data across multiple systems, improving data quality, transparency and operational efficiency. Working within a small but growing data function, this role will focus on building and optimising data pipelines, improving access to platform and event data and strengthening the underlying data architecture that supports analytics, machine learning and AI initiatives. This role is ideal for someone with strong experience across modern data engineering practices, cloud data platforms and large‑scale data processing within a SaaS or data‑driven environment.
Responsibilities
- Build, maintain and optimise scalable data pipelines that move data from operational systems into analytics platforms
- Work closely with Engineering and DevOps teams to support data replication, ingestion and reliability
- Improve access to and usability of platform logs and event data for analytics and AI use cases
- Manage and structure data stored within AWS environments including S3 and Redshift
- Develop and maintain analytics‑ready datasets using dbt as the core transformation tool
Skills and Experience
- Experience working as a Data Engineer or similar role, ideally within a SaaS or technology‑driven environment
- Strong SQL experience and confidence working with modern cloud data warehouses such as AWS Redshift
- Strong Python experience for building and maintaining production data pipelines, working with APIs, logs and semi‑structured data
- Experience using dbt to build and manage analytics models within a data warehouse
- Familiarity with AWS data services such as S3, RDS or Aurora
- Experience working with event or log‑based data sources such as Elasticsearch or OpenSearch
What's on Offer
- Salary up to £80,000 depending on experience
- Flexible remote or hybrid working
- 25 days holiday plus an additional day for your birthday
- Opportunity to work within a growing data team at a scaling SaaS organisation
Data Engineer in Southampton employer: Cyber Security training courses
Contact Detail:
Cyber Security training courses Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Southampton
✨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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving AWS, SQL, and Python. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your SQL and Python skills. Practice common data engineering problems and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented Data Engineers. Keep an eye on our job listings and make sure your application stands out by tailoring it to the role.
We think you need these skills to ace Data Engineer in Southampton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with cloud data platforms, SQL, and Python. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include any relevant projects or experiences that demonstrate your ability to build and optimise data pipelines. We love seeing real-world applications of your skills, so don’t hold back!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you're excited about the role and how you can contribute to our growing data team. Let us know what makes you a great fit for StudySmarter.
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’s super easy!
How to prepare for a job interview at Cyber Security training courses
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals. Be ready to discuss your experience with building and optimising data pipelines, especially in cloud environments like AWS. Highlight specific projects where you've improved data quality or efficiency.
✨Showcase Your SQL Skills
Since strong SQL experience is a must, prepare to demonstrate your proficiency. You might be asked to solve a problem on the spot, so practice writing queries that manipulate and retrieve data effectively. Bring examples of how you've used SQL in past roles.
✨Familiarise Yourself with dbt
As dbt is mentioned as a core tool for transformations, make sure you can talk about your experience with it. Be ready to explain how you've used dbt to build and manage analytics models, and share any challenges you faced and how you overcame them.
✨Prepare for Technical Questions
Expect technical questions related to AWS services, Python, and data architecture. Review common scenarios you might encounter in a SaaS environment. Practising coding challenges or system design questions can also help you feel more confident during the interview.