Data Engineering Lead: AI‑Driven BigQuery & Domain Data

Thg Plc; Manchester; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

25 days annual leave + bank holidays

On-site gym & facilities

Job summary

THG is seeking a Data Engineering Lead to own the architecture and delivery of data across Customer, Commercial and Operations domains. You will mentor a team of six engineers, define standards, and drive scalable, joined-up datasets that analytics and data science teams can confidently use.

You’ll work closely with Ingenuity and the Data Governance Lead to shape platform-on-top data structures and ensure data quality, governance, and AI-enabled development are embedded in practice.

Qualifications

• Hands-on, expert-level experience with BigQuery and GCP.
• Strong Python skills used daily for pipeline development.
• Experience across at least two of Customer, Commercial and Operations domains.
• Track record evolving data architecture and scalable pipelines.
• Experience with streaming or real-time data pipelines.
• Experience mentoring engineers and building CDP-like data consolidation.

Responsibilities

• Own the data engineering architecture for THG — ingested, transformed, stored and made available data across Customer, Commercial and Operations domains.
• Design consistent standards and patterns across all three domains.
• Lead the evolution of the BigQuery/GCP platform and migrations.
• Make key architectural decisions and ensure technical quality of the team’s output.
• Develop and enforce engineering standards across the team.

Skills

BigQuery

GCP

Python

Data modelling

Streaming pipelines

Tools

Dataform

dbt

Job description

THG is seeking a Data Engineering Lead to own the architecture and delivery of data across Customer, Commercial and Operations domains. You will mentor a team of six engineers, define standards, and drive scalable, joined-up datasets that analytics and data science teams can confidently use.

You’ll work closely with Ingenuity and the Data Governance Lead to shape platform-on-top data structures and ensure data quality, governance, and AI-enabled development are embedded in practice.