Lead the architecture, optimisation and evolution of our cloud-native data ecosystem. Drive platform-wide security compliance and enterprise-level data validation workflows. Improve platform scalability, reliability and operational efficiency.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Lead Data Engineer – Up to £110,000 – Fully Remote (UK)
My client, an AI‑driven eLearning platform, used globally by organisations seeking scalable, intelligent, and adaptive training solutions. Their technology leverages automation, advanced analytics, and AI‑powered personalisation to transform how enterprises deliver learning at scale. As the company continues to expand and strengthen its data capabilities, they are now searching for a Lead Data Engineer to drive the next phase of their platform evolution.
The Role
As the Lead Data Engineer, you will own the architecture, optimisation, and evolution of my client’s cloud‑native data ecosystem. This is a hands‑on leadership role where you'll guide engineering direction, ensure enterprise‑grade security and compliance, and shape the technical foundation that supports a rapidly scaling AI learning platform.
You will operate as the most senior engineer within the data function, partnering with product, engineering, security, and client‑facing teams to build a robust, modern, and scalable data platform.
Compensation & Benefits
- Salary: Up to £110,000
- Working arrangement: Fully Remote (UK)
- Bonus scheme
- Competitive annual leave package
- Company pension scheme
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Key Responsibilities
Data Architecture & Engineering
- Lead the modernisation of the data platform, including migration to Databricks—improving platform scalability and processing reliability by 40%.
- Design and implement AWS-native ETL/ELT pipelines using S3, Glue, Athena, and Step Functions to support reliable data flows across global enterprise customers.
- Build and maintain Lakehouse architecture using Apache Iceberg to support scalable analytics with ACID compliance and schema evolution.
- Consolidate multi‑tenant data environments into a unified, secure platform supporting global clients.
Data Quality, Governance & Security
- Implement enterprise-level data validation workflows that reduce downstream data issues by 60%.
- Drive platform-wide security compliance, including encryption at rest/in transit, secure deletion automation, and infrastructure security baselines.
Performance & Cost Optimisation
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- Reduce Redshift warehousing costs by up to 86% through workload optimisation and access pattern redesign.
- Improve platform operational efficiency and reduce cloud costs via architectural streamlining and modernisation.
Leadership & Team Development
- Mentor engineers, contribute to hiring, and help scale the team to meet growing product demands—supporting a 3× increase in platform usage and faster onboarding.
Required Experience
You will excel in this role if you bring:
- Deep experience building cloud‑native (AWS preferred) data platforms.
- Expertise in Databricks, Spark, AWS Glue, Athena, and Iceberg/Lakehouse architectures.
- Strong understanding of data security, compliance, and enterprise governance.
- A track record of cost optimisation, performance tuning, and scalable design.
- Experience leading engineering initiatives or mentoring teams.
- A proactive, ownership‑driven mindset suited for a fast‑scaling AI‑led product business.
- Hold active SC Clearance, or have eligibility for SC Clearance.
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