Lead Data Platform & Cloud Engineer

Job Description

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