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Data Engineering Manager

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Onsite

Data Engineering Manager

Square Enix

Data Engineering Manager

Skills

Google Cloud PlatformData EngineeringPythonGolangJavaData AnalysisAIAWSCRMGDPRComplianceAzure

2 months ago

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Important information


Location:

London, UK

Work mode:

Onsite

Published on:

3 September 2026

What they need


Who you are

  • Significant hands-on experience in software and data engineering, including backend systems, data platforms, pipelines, APIs, and integration work across batch and real-time processing
  • Experience leading engineers or small technical teams including coaching, prioritisation, and delivery guidance
  • Cloud platform experience across Google Cloud, AWS or Azure, with strong programming capability in languages such as Golang, Python or Java
  • Ability to design data systems that align with shared platforms, standards, and integration patterns
  • Able to operate in ambiguous, evolving environments with a structured, composed, and delivery-focused approach
  • Able to balance technical quality, business priorities, stakeholder needs, and delivery constraints while influencing technical, business, regional, and global teams
  • Experience working with legacy systems, existing backend environments, or complex system dependencies without disrupting business operations
  • Exposure to CRM, lifecycle communication, membership / loyalty, commerce, or marketing data use cases
  • Experience coordinating cross-functional technical projects or delivery initiatives

What the job involves

  • The Manager, Data Engineering (Marketing) helps ensure our regional marketing and customer data capabilities are ready to support better decisions, stronger engagement, and future global platform direction. The role manages regional engineering delivery for marketing and customer data platforms, translating business and analytics needs into scalable data capabilities covering integration, quality, access, technical assurance, documentation, and operational readiness
  • Working closely with regional stakeholders and global teams, the Manager ensures regional data solutions remain aligned with agreed global architecture and standards while establishing clear documentation practices, trusted operational routines, and AI-ready data capabilities that support customer engagement, better business decision-making, and future AI-enabled insight use cases
  • Responsible for coordinating and delivering agreed regional engineering priorities for marketing, customer, sales, and gameplay data, including day-to-day implementation decisions, delivery quality, technical assurance, and escalation of risks where they affect business priorities, agreed standards, or operational resilience
  • Build, operate, and improve data pipelines and core data capabilities, while supporting the transition toward shared global data platforms where applicable
  • Integrate and manage key datasets across game telemetry, account / identity, membership, commerce, CRM, and marketing systems
  • Ensure customer, player-level, and account-related data is consistent, usable, and accessible for analytics, CRM, lifecycle, membership, and campaign engagement use cases
  • Ensure data engineering delivery is carried out in line with data protection, security, secure coding, and regulatory requirements, working with Privacy, Security, Legal, and Compliance teams at agreed governance touchpoints and escalating decisions where additional approval is needed
  • Identify technical debt and limitations in existing data or backend systems, and support practical improvements that enhance scalability, maintainability, integration, and alignment with shared platform direction
  • Lead and manage a small Data Engineering team, providing coaching, prioritisation, performance guidance, and day-to-day technical leadership
  • Establish consistent documentation practices across the Data Engineering team, including technical documentation, operational runbooks, and data flow definitions, to improve transparency, maintainability, and operational continuity
  • Promote lean, efficient ways of working through automation, AI tools, clear prioritisation, and practical delivery practices

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