At a Glance
- Tasks: Architect and deliver a cloud-native data platform while leading the adoption of modern data practices.
- Company: Rapidly modernising SaaS platform with a focus on AI engineering and innovative data solutions.
- Benefits: Competitive salary, flexible remote work, and opportunities for professional growth.
- Other info: Join a dynamic team and enjoy a collaborative environment with excellent career prospects.
- Why this job: Shape the future of data platforms and influence strategic decisions across the business.
- Qualifications: Deep experience with AWS data stack and proven ability in cloud-native platform design.
The predicted salary is between 95000 - 100000 £ per year.
Reporting to the Head of Data for this global, rapidly modernising SaaS platform, this business is scaling its data capabilities to support native AI engineering and agentic workflows. We’re looking for a Senior AWS Data Engineer who wants to shape the future of their data platform, modern analytics stack, and the way data powers decisions across the business. This is a hands‑on, architecture‑shaping, strategy‑influencing role for someone who thrives at the intersection of engineering excellence, data modelling, platform design and cross‑functional leadership. You’ll own the full data lifecycle from ingestion to modelling to consumption, and play a pivotal role in building a reliable, governed, cloud‑native data ecosystem.
What you’ll be doing:
- Architect and deliver a cloud‑native data platform across ingestion, modelling, warehousing and BI
- Lead adoption of DBT, ELT patterns, AWS DMS, Redshift, Athena, Iceberg
- Build high‑quality models (Kimball, Data Vault, OBT) and set the standards for testing, documentation and governance
- Shape BI strategy and ensure consistent, trusted metrics across the business
- Mentor engineers and partner with Principal Engineers, Product and Analytics to deliver high‑value data products
- Evolve the AWS‑native platform: Redshift, Athena, S3 lake patterns, Iceberg
- Modernize DataOps: CI/CD for dbt and infra, automated testing, GitHub Actions
- Build high‑reliability ingestion pipelines with strong SLAs and schema‑change resilience
- Retire legacy pipelines and uplift performance, cost and governance
- Ensure strong security, compliance and data governance across the platform
Key requirements:
- Deep experience across the modern AWS data stack
- Proven ability to design and scale cloud‑native data platforms
- Mastery of modelling, ELT, warehouse architecture and BI tooling
- A collaborative, pragmatic leadership style with a passion for high‑quality data ecosystems.
£95k - £100k. London & 90% remote. 12-month Fixed Term Contract.
Senior Data Engineer – DBT, AWS (native), AWS DMS, ETL, Warehouse Architecture, Redshift, IaC (Terraform) in Luton employer: Smart Sourcer
Join a forward-thinking SaaS platform that is at the forefront of data innovation, where your expertise as a Senior Data Engineer will directly influence the evolution of our cloud-native data ecosystem. With a strong emphasis on collaboration and professional growth, we offer a dynamic work culture that values engineering excellence and strategic input, alongside competitive remuneration and the flexibility of 90% remote work. This role not only allows you to shape cutting-edge data solutions but also provides ample opportunities for mentorship and leadership within a rapidly modernising environment in London.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer – DBT, AWS (native), AWS DMS, ETL, Warehouse Architecture, Redshift, IaC (Terraform) in Luton
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with AWS and DBT. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ETL processes and cloud-native platforms. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with Redshift, AWS DMS, and data modelling. Practice common interview questions and have examples ready to demonstrate your expertise.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Senior Data Engineer – DBT, AWS (native), AWS DMS, ETL, Warehouse Architecture, Redshift, IaC (Terraform) in Luton
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Data Engineer role. Highlight your expertise in AWS, DBT, and data modelling to show us you’re the perfect fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re excited about this role and how you can contribute to our data platform. Share specific examples of your past work that demonstrate your hands-on experience and leadership style.
Showcase Your Projects:If you've worked on relevant projects, don’t hesitate to include them! We love seeing real-world applications of your skills, especially those involving cloud-native data platforms and modern analytics stacks.
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 this exciting opportunity to shape our data ecosystem!
How to prepare for a job interview at Smart Sourcer
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in the AWS data stack, especially DBT, Redshift, and AWS DMS. Brush up on your knowledge of ETL processes and warehouse architecture. Be ready to discuss how you've used these technologies in past projects and how they can be applied to shape the future of the company's data platform.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in data engineering and how you overcame them. Highlight your experience with building high-reliability ingestion pipelines and modernising DataOps. This will demonstrate your hands-on experience and strategic thinking, which are crucial for this role.
✨Emphasise Collaboration and Leadership
Since this role involves mentoring engineers and working cross-functionally, be ready to talk about your leadership style. Share instances where you’ve successfully collaborated with product and analytics teams to deliver high-value data products. This will show that you can thrive in a team-oriented environment.
✨Prepare Questions That Matter
Think of insightful questions to ask during the interview. Inquire about the company’s vision for their data platform and how they see the role evolving. This not only shows your interest but also helps you gauge if the company aligns with your career goals and values.
