Security Analytics Engineer

sonyinteractiveentertainmentglobal·Londonmid

En corto

→Ingeniero de análisis de seguridad que construye y mantiene pipelines de datos confiables en Snowflake.
→Trabaja con datos de seguridad, tecnología y negocio para generar información lista para análisis y AI.
→Destaca por su enfoque en infraestructura de datos, automatización y calidad de datos para soportar decisiones estratégicas.

Fluent English required for collaboration with global teams.

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

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¿Qué piden?

✓Experiencia en diseño e implementación de pipelines de ingesta y transformación de datos.
✓Conocimiento sólido de Snowflake (data models, warehouse, objetos)
✓Habilidades en automatización de procesos de datos
✓Aplicación de prácticas de ingeniería de software a código de datos (versionado, pruebas, CI)
✓Capacidad para operar y monitorear pipelines en producción
✓Experiencia con datos de seguridad o entornos de ciberseguridad

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

SnowflakePythonSQLGitCI/CDAirflowREST APIsJSONYAMLDocker

¿A quién escribirle en sonyinteractiveentertainmentglobal?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Job description The successful candidate will join the Security Data Analytics team, working across PlayStation data assets and business groups. This team develops the data products, pipelines, dashboards, and reporting that help Information Security teams understand security posture, risk trends, control effectiveness, exposure, and remediation progress. Our work is increasingly built on automation and AI-enabled analytics, and this role builds the data foundations that make that possible. This opening focuses on the backend of that work. Reporting to the Director of Security Data Analytics, you will design and operate the data engineering foundations our analytics depend on: ingestion and transformation pipelines, Snowflake data models, automation, and the enrichment and AI-ready data patterns that turn raw security signals into trusted, analytics-ready data. Presentation-layer engineers own most visualization delivery, so your primary contribution is the reliability, structure, and performance of the data layer, including keeping it running day to day. This is a technical, individual contributor role. You will solve moderately complex problems with limited supervision and own a discrete workstream or a sub-set of a larger effort, working closely with a global set of stakeholders. This role is UK-based and remote-eligible. Responsibilities • Design, build, and optimize data ingestion, transformation, and enrichment pipelines that turn security, technology, and business data into trusted, analytics-ready data. • Build and maintain Snowflake data models and warehouse objects that support reporting, visualization, automation, and AI-enabled use cases. • Develop automation that reduces manual data handling and reporting effort and improves reliability across the platform. • Prepare AI-ready data and support AI-enabled analytics and reasoning workflows built on our data platform. • Add business and technical context to security data to improve prioritization and decision-making. • Apply software engineering practices to data and analytics code, including version control, testing, code review, and CI. • Run and support the team's pipelines and data products in production: monitor health

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