Fremantle

Data engineer in social video

In short

Mid-level Data Engineer role at Fremantle's Social Video team, building and owning data pipelines that integrate performance, advertising, platform, audience and content data from YouTube, Meta and other global sources using BigQuery and dbt. The company is a media production business, and this role demands strong SQL, Python, cloud data platform experience and hands-on API integration skills. Office-based in London, full-time, with benefits including pension, EV scheme and season ticket loan.

Описание
We're looking for a strong mid-level Data Engineer to support our well-established Social Video team. You'll design, build and optimise the data pipelines that bring together performance, advertising, platform, audience and content data from multiple global sources into our data environment. This role suits someone who already has solid hands-on experience and is ready to step up and take ownership of bigger systems, shaping how our data is structured, and helping us connect the dots across a key part of the business.
Задачи
•Ingest and integrate new data sources, including advertising, audience, platform, and content from social partners into Fremantle's central data platform
•Own the YouTube and Meta data pipelines, including Content ID / CMS reports, so revenue and performance data reaches Finance complete, reconciled and on time for month-end
•Build and maintain robust, scalable data pipelines, using technologies such as Google BigQuery and dbt to transform raw data into structured, analytics-ready datasets
•Ensure data integrity, governance, and security across the data platform, contributing to data quality assurance through validation and testing frameworks
•Collaborate with the central Data & Analytics team to structure datasets for BI dashboards and reporting
•Optimise data pipelines for performance, scalability, and efficiency, following standard engineering practices including version control, code reviews and iterative development
•Monitor pipeline health, data freshness and data quality, with proactive alerts and issue resolution
•Document pipelines, datasets and data flows to ensure clarity, reproducibility and smooth handovers across teams
•Translate business and analytical needs into clear data models and technical solutions
•Adapt pipelines to evolving platform and partner data, including handling schema changes and irregular data feeds
•Automate data processes to reduce manual intervention and streamline operations
•Stay current with modern data engineering technologies and best practices, contributing to continuous improvement and knowledge sharing across the team
Требования
•Proven experience working with cloud-based data platforms (e.g., GCP, Azure, AWS, Snowflake)
•Strong proficiency in SQL and Python, with the ability to write complex queries and reusable scripts for data transformation, validation, testing and automation, ensuring data accuracy, reliability and efficiency
•Experience designing and managing robust ETL/ELT pipelines using tools such as dbt, BigQuery or equivalent technologies
•Experience with Git-based version control, CI/CD tooling and collaborative development practices, including code reviews and testing
•Hands-on experience retrieving and integrating data from APIs (REST, JSON), including handling authentication, pagination, rate limits and changing data structures
•Solid understanding of data modelling principles and best practices for structuring data for analytics, reporting and downstream consumption
•Confident working with large, complex datasets across various formats (databases, Excel, CSV, JSON, Parquet, APIs), while optimising performance
•Strong problem-solving skills and a track record for diagnosing and resolving complex data-related issues
•Excellent communication and collaboration skills. You're comfortable engaging with analysts, stakeholders, and cross-functional teams
•A genuine curiosity about how data drives programming decisions, content performance, audience behaviour and monetisation
Будет плюсом
•Microsoft Fabric is a plus
•Experience with the YouTube Analytics / Reporting and Meta Graph APIs, and with finance-grade data: reconciliation, controls and hard deadlines an advantage
•Experience integrating data from social platforms such as YouTube and Meta, or working with advertising, audience, performance and revenue data would be advantageous
Условия
Our benefits include generous company pension, summer Fridays, audience tickets, employee assistance program, access to free courses and training, EV scheme, cycle to work scheme, season ticket loan, business coaching sessions and volunteer days.

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