At a Glance
- Tasks: Lead a team to enhance marketing and customer data capabilities for better decision-making.
- Company: Join Square Enix, a leading entertainment publisher known for iconic worlds and stories.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on innovation and collaboration.
- Why this job: Make an impact in the gaming industry by shaping data solutions for global engagement.
- Qualifications: Experience in data engineering, team leadership, and cloud platforms like AWS or Google Cloud.
The predicted salary is between 63000 - 77000 £ per year.
Job Description
Square Enix is a leading publisher of entertainment content, known for creating iconic worlds, characters, and stories that connect with players around the world.
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.
Responsibilities & KPI's
- 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.
Qualifications and Skills
Essential
- 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.
Desirable
- 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.
- Purpose & Values
- Purpose: Creating New Worlds with Boundless Imagination to Enhance People’s Lives.
• Values
- Deliver Unforgettable Experiences
- Embrace Challenges
- Act Swiftly
- Stronger Together
- Continuously Evolve
- Cultivate Integrity
- #J-18808-Ljbffr
Manager, Data Engineering (Marketing) employer: Square Enix, Inc.
Square Enix is an exceptional employer that fosters a dynamic and innovative work culture, where creativity and collaboration thrive. As a Manager in Data Engineering (Marketing), you will have the opportunity to lead a talented team while contributing to the development of cutting-edge data solutions that enhance customer engagement and business decision-making. With a commitment to employee growth, Square Enix offers robust training programs and a supportive environment that encourages continuous evolution and integrity, making it a rewarding place to build your career in the heart of the entertainment industry.
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We think this is how you could land Manager, Data Engineering (Marketing)
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We think you need these skills to ace Manager, Data Engineering (Marketing)
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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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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.
