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- Tasks: Lead the migration and modernisation of data platforms in AWS, focusing on AI enablement.
- Company: Join a forward-thinking tech company at the forefront of cloud innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with opportunities to lead and innovate in a collaborative environment.
- Why this job: Make a significant impact by driving cutting-edge data solutions and AI initiatives.
- Qualifications: 5+ years in cloud or data engineering with strong AWS and DevOps skills.
The predicted salary is between 80000 - 100000 £ per year.
The Lead Data Platform & Cloud Engineer will own and deliver the end-to-end technical execution of a data migration and platform modernisation and AI enablement programme in AWS. This role is best suited to a well-rounded cloud/platform engineer with strong DevOps and infrastructure expertise, who can operate across data migration, platform engineering, MLOps/AI enablement, and modern cloud-native development in AWS. The focus is initially on DevOps, infrastructure, and platform engineering, enabling scalable, secure, and automated migration and ingestion of enterprise data. Building a foundation for enabling scalable machine learning and AI-driven use cases (MLOps) is the ultimate goal.
Key Responsibilities
- Own and evolve the AWS/CDP architecture for data migration, ingestion, feature engineering and downstream AI/ML consumption
- Define and enforce engineering standards (Terraform, CI/CD, pipeline design, naming conventions)
- Define and implement MLOps architecture and standards, including model training, deployment and monitoring workflows (e.g. SageMaker pipelines)
- Lead platform engineering and infrastructure delivery (IaC, networking, security, environment setup)
- Lead and deliver the migration of ~8–10 enterprise databases into AWS using DMS and CDC patterns
- Ensure migration pipelines are scalable, automated, and resilient
- Enable event-driven and batch data and ML pipelines (S3, Lambda, orchestration), including pipelines that support MLOps
- Enable AI and advanced analytics by ensuring data is discoverable, high quality and structured for ML consumption
- Ensure data lineage, cataloguing, and documentation are captured
- Coordinate backlog prioritisation, sprint planning, and delivery sequencing
- Validate deliverables for quality, performance, security, and operational readiness
- Act as senior technical interface with stakeholders and delivery partners
- Lead knowledge transfer and upskilling of engineers
Required Experience & Skills
- 5+ years in cloud, platform or data engineering roles, including leadership experience
- Strong AWS experience: S3, Lambda, IAM, VPC/networking, DMS
- Proven experience with Infrastructure-as-Code (Terraform) and CI/CD pipelines
- Strong Python and SQL skills
- Understanding of data platforms (e.g. Snowflake/CDP) and ingestion pipelines
- Hands-on experience with AI/ML and MLOps frameworks (e.g. AWS SageMaker) and supporting infrastructure for model training, deployment
- Experience designing or supporting MLOps practices, including CI/CD for ML, model versioning, monitoring
- Understanding of data requirements for ML, including feature engineering, training data pipelines and data quality considerations
- Familiarity with modern development and deployment frameworks
- Strong stakeholder communication and technical leadership skills
- Experience delivering large-scale data migrations, including CDC approaches
- Experience in the Energy Sector (nice to have)
- Experience with dbt / ELT patterns (nice to have)
- Experience with C# (nice to have)
Ideal Profile
- Broad technologist with a DevOps / platform engineering or cloud architecture background, with exposure to AI/ML or data science workflows
- Comfortable working across infrastructure, data platforms, and application layers
- Experience supporting or enabling modern workloads, including AI/ML pipelines
- Able to move between hands-on delivery and technical leadership
Lead Data Platform & Cloud Engineer in London employer: Vallum Associates
Contact Detail:
Vallum Associates Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Platform & Cloud Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to AWS, Terraform, and MLOps. We want to see what you can do, so make it easy for us to find!
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and soft skills. We love candidates who can communicate complex ideas clearly, so practice explaining your past projects and how they relate to the role.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always looking for passionate individuals who are ready to take on challenges in cloud engineering and AI.
We think you need these skills to ace Lead Data Platform & Cloud Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Lead Data Platform & Cloud Engineer. Highlight your experience with AWS, DevOps, and MLOps, and don’t forget to mention any relevant projects that showcase your skills in data migration and platform engineering.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you’re the perfect fit for this role. Share specific examples of your past experiences that align with our needs, especially around cloud-native development and AI enablement.
Showcase Your Technical Skills: We want to see your technical prowess! Make sure to list your strong AWS experience, Infrastructure-as-Code knowledge, and any hands-on work with AI/ML frameworks. This is your opportunity to demonstrate how you can lead our data migration and platform modernisation efforts.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Vallum Associates
✨Know Your AWS Inside Out
Make sure you brush up on your AWS knowledge, especially around S3, Lambda, and DMS. Be ready to discuss how you've used these services in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your DevOps Skills
Prepare to talk about your experience with Infrastructure-as-Code, particularly Terraform, and CI/CD pipelines. Have specific examples ready that demonstrate how you've implemented these practices to improve efficiency and scalability in previous roles.
✨Demonstrate MLOps Understanding
Since this role involves AI enablement, be prepared to discuss your experience with MLOps frameworks like AWS SageMaker. Highlight any projects where you've designed or supported ML pipelines, focusing on model training, deployment, and monitoring.
✨Communicate Like a Pro
Strong stakeholder communication is key for this position. Practice articulating complex technical concepts in a way that's easy to understand. Think of examples where you've successfully led discussions or knowledge transfers with both technical and non-technical audiences.