Data Engineer - Enterprise Streaming & Content

Data Engineer III (Enterprise Streaming & Content Analytics) Location: London Liverpool Street, Onsite Duration: 12-Month Contract The Opportunity: We are looking for a Senior Data Engineer (Level III) to join one of the world’s leading digital entertainment and premium streaming giants. Operating in over 240 countries, this global brand delivers thousands of movies, TV shows, live sports, and original content to millions of users daily. Based in their state-of-the-art London office near Liverpool Street (5 days a week onsite), you will sit within the Content Analytics & Products team. You will design, build, and operate the massive, scalable data pipelines and models that power customer-facing features and global internal analytics. What You’ll Do: • Build & Optimize: Design robust ETL/ELT pipelines to ingest and transform disparate data streams, handling both traditional batch and live event data. • Scale with Big Data: Leverage heavy cloud infrastructure to process massive datasets efficiently. • Infrastructure as Code: Maintain and develop the data platform using modern infrastructure-as-code frameworks. • Collaborate & Innovate: Partner with software engineers, data scientists, and business stakeholders to translate complex requirements into high-performance technical solutions. • Quality & Performance: Implement automated data quality frameworks to detect anomalies and optimize storage/processing costs. What You Need to Bring: • Core Engineering: Strong track record in a Data Engineering or software engineering role, with deep knowledge of the full software development lifecycle (SDLC), code reviews, and testing. • Programming & SQL: Expert-level SQL skills and proficiency in at least one modern scripting language (Python, Java, Scala, or Node.js.) • Big Data & Pipelines: Proven experience building and operating highly available distributed systems for large-scale data extraction and data warehousing. • Cloud Infrastructure: Strong familiarity with cloud-native big data ecosystems—specifically managed warehousing, object storage, compute clusters, and event-streaming technologies (e.g., Redshift, S3, EMR, Spark, Kinesis).