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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - Full Stack - **Company:** ESL FACEIT GROUP - **Location:** London, UK (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Automation of Tests, BigQuery, Cloud Computing, Cloud Database, Cloud Engineering, Code Review, Continuous Integration, Data Architecture, Data Infrastructure, Data Integrity, Dataspaces, Data Warehousing, Database Development, Dimensional Modeling, Video Game Development, Identity and Access Management, Python (Programming Language), Package Management Systems, Raw Data, SQL Databases, Data Streaming, Workflow Management Systems, Computer Gaming, Data Processing, Infrastructure as Code (IaC), Data Layers, Infrastructure Automation Frameworks, Machine Learning Operations, Software Version Control, Programming Languages - **Published:** June 18, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=047829d0012aaf7f ## About the Role Do you have experience in SQL?, * Expert Technical Skills: Mastery of SQL and advanced Python/programming languages for high-performance data processing; * Modern Data Stack (MDS) Expertise: Deep, hands-on experience with cloud data warehouses (e.g., BigQuery internals), workflow orchestration platforms, and dbt optimisation at scale (macros, package management); * Data Architecture & Infra: Proven track record in dimensional modeling, cloud architecture patterns, Identity and Access Management (IAM), networking, and Infrastructure as Code (IaC); * AI & Industry Awareness: Substantial awareness of the evolving data ecosystem, combined with practical experience building AI agents and prompting AI effectively; * Project Leadership: Demonstrated success in leading end-to-end projects, mitigating risks within deployment cycles, and managing cross-functional technical delivery; * Communication Excellence: Superb technical storytelling skills; ability to balance deep technical details with strategic business context for both engineering teams and non-technical stakeholders; * Collaboration & Soft Skills: Technical leadership, strategic thinking, ownership mentality, attention to detail, and a passion for enabling self-service and data quality. Bonus skills * Experience with real-time inference and streaming data architectures; * Familiarity with MLOps platforms (MLflow, Vertex AI, etc.); * Understanding of responsible AI, security, and compliance considerations; * Passionate about learning new, cutting-edge technologies and finding applicable business cases as needed; * A passion for video games and esports is a plus. ## Description The Senior Data Engineer is a versatile technical leader who owns the entire end-to-end data lifecycle. You bridge the gap between raw cloud infrastructure and business intelligence by designing both the extraction pipelines and the warehouse semantic layers. As a true hybrid engineer, you don't just move raw data; you transform it into a trusted, scalable, and AI-ready asset. This role is a critical driver of EFG's core mission centered on Automation, Integrity, and Cognitive Modelling., * End-to-End Architecture & Delivery: Define, design, and implement complex data infrastructure, pipeline ingestion, and transformation layers spanning multiple business units (Esports, Festivals, Commerce, HR, Finance, and FACEIT); * Pipeline & Platform Engineering: Construct scalable architectures using well-architected framework principles (reliability, security, performance, and automation). Manage workflow orchestration, CI/CD pipelines, and infrastructure automation; * Data Modeling & Semantic Layers: Standardise enterprise-grade dimensional modeling (Kimball/Inmon), star schemas, and centralised semantic layers to define trusted, cross-pillar metrics; * AI-Ready Datasets: Create clean, optimised, AI-ready datasets with structured metadata, clear naming conventions, and explicit documentation to support downstream AI agents and cognitive models; * Technical Standards & Governance: Establish and enforce best practices for Python/SQL development, dbt optimisation, testing frameworks, and version control across the hybrid data domain; * Efficiency & Cost Optimisation: Proactively monitor and optimise performance and infrastructure platform costs across storage, compute, and querying layout (e.g., BigQuery configurations); * Stakeholder Partnership: Act as a strategic partner to business leaders and analysts, translating complex objectives into scalable self-service data products; * Incident Response & Data Integrity: Lead incident response efforts for both system downtime and data quality anomalies, implementing automated testing to ensure Industry Standard Data Integrity; * Mentorship & Growth: Mentor junior and mid-level engineers through rigorous code reviews and technical guidance, supporting their professional growth and advancing team standards. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Harnessing the Power of Open Source's Newest Technologies](https://www.wearedevelopers.com/videos/1448-harnessing-the-power-of-open-source-s-newest-technologies) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Making Data Warehouses fast. 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