At a Glance
- Tasks: Architect and deliver a cloud-native data platform while leading BI strategy and mentoring engineers.
- Company: Rapidly modernising SaaS platform with a focus on AI engineering and innovative data solutions.
- Benefits: Competitive salary, 90% remote work, and opportunities for professional growth.
- Other info: 12-month Fixed Term Contract with excellent career advancement potential.
- Why this job: Shape the future of data platforms and make impactful decisions in a dynamic environment.
- Qualifications: Deep experience with AWS data stack and strong leadership skills in data ecosystems.
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 Aberdeen 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 career advancement in a rapidly modernising environment.
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 Aberdeen
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering space, 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 to boost your confidence!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Senior Data Engineer – DBT, AWS (native), AWS DMS, ETL, Warehouse Architecture, Redshift, IaC (Terraform) in Aberdeen
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior Data Engineer. Highlight your experience with AWS, DBT, and data modelling. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to shaping our data platform. Let us know why you're excited about this opportunity at StudySmarter.
Showcase Your Projects:If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work with ETL processes, Redshift, or any cloud-native solutions. We love seeing real-world applications of your skills.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. We can’t wait to hear from you!
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.
✨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.
✨Emphasise Collaboration and Leadership
Since this role involves mentoring and cross-functional leadership, be prepared to talk about your collaborative experiences. Share instances where you’ve partnered with engineers, product teams, or analytics to deliver impactful data products.
✨Understand the Business Impact of Data
Be ready to discuss how data influences decision-making within a business context. Show that you understand the importance of governance, compliance, and security in building a trusted data ecosystem. This will align with the company’s goal of shaping their data platform for AI engineering.
