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 remote work, 25 days holiday plus birthday off.
- Other info: Exciting opportunity for career growth in a supportive environment.
- Why this job: Join a dynamic team and make an impact in the world of data analytics.
- Qualifications: Experience in data engineering, strong SQL and Python skills required.
The predicted salary is between 80000 - 80000 £ per year.
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
- 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
- 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
This is just a brief overview of the opportunity. To learn more, simply apply with your CV and we'll be in touch to discuss the role in more detail.
Cloud Data Engineer for SaaS Analytics (Remote/Hybrid) employer: Cyber Security training courses
Join a dynamic and innovative B2B SaaS organisation that prioritises data integrity and offers a collaborative work culture. With flexible remote or hybrid working options, generous holiday allowances, and a focus on employee growth within a rapidly expanding data team, this company is dedicated to fostering a supportive environment where your contributions directly impact the success of cutting-edge analytics and AI initiatives.
Contact Details:
Cyber Security training courses Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Cloud Data Engineer for SaaS Analytics (Remote/Hybrid)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect 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 pipelines, projects, or any cool analytics work you've done. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and common data engineering questions. Practice explaining your past projects and how they relate to the role you're applying for.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to join our growing team.
We think you need these skills to ace Cloud Data Engineer for SaaS Analytics (Remote/Hybrid)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Cloud Data Engineer role. Highlight your experience with data pipelines, AWS, and any relevant projects that showcase your skills in a SaaS environment. We want to see how you fit into our world!
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples of how you've built or optimised data pipelines, worked with SQL, or used dbt. This helps us understand your hands-on experience and how you can contribute to our team.
Keep It Clear and Concise:We appreciate clarity! Keep your application straightforward and to the point. Avoid jargon unless it’s relevant to the role. A well-structured application makes it easier for us to see your potential.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It streamlines the process for us and ensures your application lands in the right hands. We can’t wait to hear from you!
How to prepare for a job interview at Cyber Security training courses
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially SQL, Python, and AWS services. Brush up on your experience with data pipelines and cloud data platforms, as these will likely be key discussion points during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you overcame them. Think about examples where you optimised data pipelines or improved data quality, as this will demonstrate your hands-on experience and analytical thinking.
✨Understand the Company’s Mission
Research the company’s focus on marketing data integrity and how they automate data flows. Being able to articulate how your skills align with their goals will show that you’re genuinely interested in the role and understand their business.
✨Prepare Questions for Them
Have a few insightful questions ready to ask at the end of the interview. This could be about their data architecture, team dynamics, or future projects. It shows that you’re engaged and eager to learn more about how you can contribute to their success.
