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# Lead Data Engineer

- **Company:** VIQU Ltd
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Audit Trail, Microsoft Azure, Cloud Database, Code Generation, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Profiling, Data Structures, DevOps, Dimensional Modeling, Github, Python (Programming Language), PostgreSQL, Machine Learning, Metadata, SQL Databases, Transact-SQL, Data Logging, Model Validation, Git, Data Layers, Build Management, Git Flow, Data Pipelines
- **Published:** September 30, 2026
- **Apply:** https://www.totaljobs.com/job/lead-data-engineer/viqu-it-recruitment-job108060178

## About the Role

* First-class STEM degree from a prestigious university
 * 5+ years in Data Engineering/Platform roles, 2+ years in a lead or senior capacity
 * Proven line management experience - not just technical leadership
 * Track record of building or improving engineering processes and team structures
 * Expertise in SQL pipelines, Python orchestration, dimensional modelling, and star/snowflake schemas
 * Experience with cloud data infrastructure, CI/CD automation, and metadata frameworks
 * Comfortable working across product, AI, and client delivery teams

## Description

Function Leadership & Team Management

 * Own the Data Engineering function: standards, tooling, and delivery processes
 * Manage, mentor, and develop a team of data engineers including performance and development plans
 * Lead recruitment and be the engineering voice in cross-functional planning

Data Engineering & Architecture

 * Design and build high-performance ETL/ELT pipelines across operational, analytical, and AI data layers
 * Lead schema design, model validation, scalable partitioning, and metadata-driven SQL frameworks
 * Hands-on ownership of the most complex implementation work

Data Modelling & Design

 * Define and evolve data models powering SCV, segmentation, AI features, and analytics
 * Work across dimensional, event-based, and ML-aligned data structures

DevOps, CI/CD & AI Ops

 * Own CI/CD for data pipelines using Git-based workflows, deployment governance, and rollback handling
 * Orchestrate ML model outputs into production pipelines with resilience controls
 * Drive AI tooling adoption across engineering: code generation, data profiling, documentation, and testing
 * Implement structured logging, alerting, SLA tracking, and access control

Key Technologies

 * Cloud: Azure, AWS, or GCP | SQL (T-SQL, PostgreSQL), Python, versioned metadata frameworks
 * DevOps: Git, CI/CD (Azure DevOps, GitHub Actions) | Monitoring: Custom logging, alerts, structured failure handling
 * Security: Role-based schema access, PII isolation, audit trails


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