Exec Capital Recruitment
IT Engineer – Data Pipelines and Infrastructure
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Description
Location: London (hybrid)
Employment type: Full-time
Package: £55,000–£75,000
Reporting to: Founder/CEO
The Opportunity
Our client is a London-based youth-culture media group whose brands reach an audience of more than 120 million people every month, producing work for 75+ global brand partners. The business is building out a first-party behavioural data engine that turns what its audience watches, joins and responds to into structured, consented signal.
This role is focused on the practical, day-to-day engineering that keeps that data engine running: building and maintaining the pipelines, keeping the infrastructure reliable, and turning agreed designs into working systems.
The Role
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You will build and operate the automated pipelines that feed the company's data warehouse from social platform APIs, web analytics, newsletter/CRM and campaign reporting sources. You'll work to schemas and governance standards set by the senior technical lead on the project, focusing on reliable delivery, clean implementation and day-to-day operational ownership.
Responsibilities
What You'll Do
- Build and maintain automated ELT pipelines pulling from TikTok, Instagram, YouTube and other platform APIs, Google Analytics, newsletter/CRM and commerce sources
- Implement agreed data schemas and cohort structures consistently across sources
- Monitor pipeline health, handle schema drift and API changes, and fix issues as they arise
- Apply data governance rules already defined for the project — retention windows, consent flags, provenance tagging
- Support the team building the internal behavioural dashboard with clean, reliable data feeds
- Produce regular data health reporting
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Qualifications
What We're Looking For
- 1-4 years' experience building or maintaining production data pipelines
- Solid SQL and Python
- Experience working with third-party APIs — social platform API experience a plus
- Familiarity with a cloud data warehouse (e.g. BigQuery or Snowflake) and ELT tooling (e.g. Fivetran, Airbyte, dbt)
- A methodical, reliable approach to operational work and a willingness to follow data governance standards closely
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