Lead Data Engineer

Experis UK; Greater London; On-site; GBP 85,000 - 120,000; Full time

Job summary

Experis UK is seeking a Lead Data Engineer to drive the design and delivery of enterprise-scale data solutions on Google Cloud Platform. You will guide ETL/ELT development, data models, and integration frameworks while promoting best practices across CI/CD and cloud automation.

As a senior leader, you will mentor engineers, optimise data workflows, and ensure security, governance, and performance across cloud environments. Strong Python, BigQuery, and IaC experience are essential.

Qualifications

• Experience with enterprise-scale data engineering on cloud platforms.
• Strong knowledge of data modeling and ETL/ELT design.
• Experience with IaC and cloud automation tools.

Responsibilities

• Lead the design and delivery of enterprise-scale data engineering solutions within Google Cloud Platform (GCP).
• Develop and maintain scalable ETL/ELT pipelines, data models, and integration frameworks.
• Design and manage Infrastructure as Code (IaC) solutions using Terraform.
• Build and support automated deployment processes through GitLab CI/CD pipelines.
• Design, optimise, and maintain BigQuery datasets, schemas, and analytical workloads.
• Develop and manage Cloud Storage, Cloud SQL, and Cloud Composer solutions.
• Develop Python-based ETL applications, automation tools, and data services.
• Implement real-time data integration and Change Data Capture (CDC) solutions using Striim.
• Develop and support ETL workflows and reusable components using Ab Initio.
• Ensure data quality, governance, security, and compliance standards are maintained.
• Monitor platform performance, reliability, and operational efficiency across cloud environments.
• Lead code reviews, mentor engineers, and establish engineering best practices.
• Collaborate with cross-functional teams to deliver secure, reliable, and scalable data solutions.
• Support architecture design, technical planning, estimation, and continuous improvement initiatives.

Skills

GCP

BigQuery

Terraform

GitLab CI/CD

Python

Data modelling

CI/CD

Tools

Ab Initio

Job description

Overview

This is an opportunity to join a leading organisation undertaking a major cloud transformation and data modernisation programme, delivering enterprise-scale data solutions across a complex technology landscape.

As a Lead Data Engineer, you will provide technical leadership across the design, development, automation, and optimisation of cloud-based data platforms, ensuring secure, scalable, and high-performing solutions are delivered to support business and operational objectives.

Working closely with architects, stakeholders, analysts, and engineering teams, you will drive best practice across data engineering, infrastructure automation, CI/CD, and cloud technologies while mentoring and leading other engineers within the delivery team.

Key Responsibilities

• Lead the design and delivery of enterprise-scale data engineering solutions within Google Cloud Platform (GCP).
• Develop and maintain scalable ETL/ELT pipelines, data models, and integration frameworks.
• Design and manage Infrastructure as Code (IaC) solutions using Terraform.
• Build and support automated deployment processes through GitLab CI/CD pipelines.
• Design, optimise, and maintain BigQuery datasets, schemas, and analytical workloads.
• Develop and manage Cloud Storage, Cloud SQL, and Cloud Composer solutions.
• Develop Python-based ETL applications, automation tools, and data services.
• Implement real-time data integration and Change Data Capture (CDC) solutions using Striim.
• Develop and support ETL workflows and reusable components using Ab Initio.
• Ensure data quality, governance, security, and compliance standards are maintained.
• Monitor platform performance, reliability, and operational efficiency across cloud environments.
• Lead code reviews, mentor engineers, and establish engineering best practices.
• Collaborate with cross-functional teams to deliver secure, reliable, and scalable data solutions.
• Support architecture design, technical planning, estimation, and continuous improvement initiatives.