IT & Software

IT Engineer – Data Pipelines and Infrastructure

Exec Capital Recruitment

London · England · United Kingdom

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

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

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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Reference: WJ-766_22197078

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