At a Glance
- Tasks: Build and maintain automated data pipelines from social platforms and analytics sources.
- Company: Youth-culture media group in London with a massive audience reach.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Exciting environment with a focus on innovation and collaboration.
- Why this job: Join a dynamic team and work on impactful data projects that shape youth culture.
- Qualifications: 1-4 years of experience in data pipelines, solid SQL and Python skills required.
The predicted salary is between 63000 - 77000 £ per year.
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 signals.
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
- 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
- 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.
IT Engineer – Data Pipelines and Infrastructure employer: Exec Capital Recruitment
As a Fractional Business Development Operator at this boutique advisory firm, you'll be part of a dynamic and innovative team that values expertise and collaboration. With a remote working model and flexible engagement, the company fosters a supportive work culture that prioritises employee growth and development, offering you the chance to build essential business infrastructure from the ground up. This role not only provides competitive day rates but also the unique opportunity to shape the firm's future in a high-value, relationship-driven market.
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We think this is how you could land IT Engineer – Data Pipelines and Infrastructure
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We think you need these skills to ace IT Engineer – Data Pipelines and Infrastructure
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Exec Capital Recruitment. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
