Senior Data Engineer

tripadvisor·Londonsenior

En corto

→Ingeniero de datos senior que construye infraestructura de datos a escala petabyte para una plataforma de viajes global.
→Diseña y mantiene pipelines de datos batch y streaming, modelos y herramientas de gobernanza con enfoque en calidad y confiabilidad.
→Destaca por liderar soluciones end-to-end con impacto directo en GenAI, análisis y machine learning.

Fluent English required for collaboration across global teams.

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¿Qué piden?

✓Experiencia sólida en ingeniería de datos con enfoque en plataformas escalables.
✓Conocimiento profundo de ETL, pipelines batch y streaming, y arquitectura de datos.
✓Habilidades sólidas en ingeniería de software y diseño de sistemas confiables.
✓Experiencia con Snowflake, BigQuery y/o Hive para datasets a gran escala.
✓Capacidad para liderar incidentes, análisis de causas raíz y monitoreo de SLAs.
✓Colaboración estrecha con equipos de datos, análisis y machine learning.

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

SnowflakeBigQueryHiveApache AirflowApache SparkKafkaDockerKubernetesGitAWS

¿A quién escribirle en tripadvisor?

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

About Tripadvisor The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork. Our Data Platform team is the engineering backbone of Tripadvisor’s data ecosystem. Formed from the core fundamentals of our Data Engineering and Software Engineering (Data Platform) groups, this unified team combines deep data pipeline expertise with robust platform engineering capabilities. We are responsible for providing the software and infrastructure that enable Tripadvisor to better understand visitor preferences and drive GenAI, Analytical, and DSML initiatives at petabyte scale. We build the frameworks, infrastructure, tooling, data modeling, and best practices that ensure consistent, well-governed, high-quality data products everywhere; and we directly own a deliberate set of business-critical, cross-cutting data products. Our work spans: • Streaming and batch data platforms that unlock data across Tripadvisor • ETL pipelines and data models serving terabytes and growing datasets in Snowflake, BigQuery, and Hive • Orchestration, scheduling, and ETL generation tools to support cloud migrations and petabyte-scale operations • Tracking instrumentation, information architecture, and data governance tooling for business-critical analytics • Self-service and agentic analytics capabilities — governed, natural-language access to trustworthy data The Role Tripadvisor is looking for a Senior Data Engineer to join our fast-moving Data Platform group. In this role, you will design, build, and sustain the data infrastructure that powers the world’s most trusted travel platform. You'll pair strong software engineering fundamentals with deep data engineering expertise, set technical direction, architecting reliable pipelines, and delivering end-to-end solutions that scale to hundreds of millions of travelers. Do you enjoy building features end-to-end? Do you thrive working with a broad technology stack, releasing frequently, and collaborating with talented engineers worldwide? If so, we’d love to talk. We collaborate closely with Product, Analytics, Data Science, CRM, Marketing, Finance, and Machine Learning teams across Tripadvisor’s global engineering organization. What You'll Do Data Engineering & Data Products & Enablement • Own the full lifecycle of business critical data pipelines: define SLAs, implement performance measurement, monitoring, alerting, and anomaly detection, and lead incident response and root-cause analysis. <li sty

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