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UK remote

Senior Data Engineer

TripadvisorLondon, United Kingdom - Remote / HybridPosted 2 Aug 2026

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About this role

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.

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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.

Define scalable, reusable data models and curated data sets for analytics, data science, CRM, machine learning, and other data consumers across the organization. Design, build, and maintain robust ETL/ELT data pipelines that process terabyte- to petabyte-scale data across Snowflake, BigQuery, and other platforms. Design, build and maintain streaming and batch systems that power real-time and analytical workloads, and lead simplification of legacy ingestion paths.

Drive warehouse standardization and technical-debt reduction as we consolidate toward one warehouse. Drive enterprise data integrity, validation, documentation, and governance practices — and the tooling that makes them the default rather than the exception. Apply AI to accelerate the team's own work (e.g., building reusable Claude skills for pipeline migrations and upgrades) and share those patterns with individual teams.

Set and evolve engineering standards, patterns, and best practices for data modeling, pipeline design, testing, and observability. Platform & Software Engineering Write and review production Java and Python code across our evolving platform stack — from data ingestion and event processing to REST services and internal tooling Architect and scale streaming and batch processing systems (Flink, Spark, Kafka) that power real-time and analytical workloads.

Take responsibility for all aspects of software engineering: design, implementation, QA, and maintenance, with a CI/CD mindset (most engineers release to production every few days). Design, operate, and continuously improve cloud infrastructure on AWS, applying strong judgment on performance, scalability, and cost. Technical Leadership, Collaboration & Ownership Lead large size initiatives end to end: technical specs, design reviews, project planning, and delivery across teams.

Set and uphold code and data quality through leadership in design and code review, and act as a technical mentor to engineers on the team and in the domains you enable. Translate ambiguous, cross-organizational data problems into clear, standardized solutions, and communicate effectively with both technical and business stakeholders. Work with independence and a mandate to leave things better than you found them, in a fast-paced, globally distributed environment.

Partner with Product, Design, Analytics, and Data Science leaders to shape specifications, challenge requirements constructively, and deliver high-impact solutions. Skills & Experience 8+ years of data engineering or software development experience in a commercial setting, including a track record of technical leadership on medium-to-large projects. Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

Experience taking significant projects from design through production, with growing ownership of technical direction Deep experience designing and implementing complex ETL/ELT from concept to production, including SLAs, performance measurement, and monitoring. Comprehensive data design and data modeling experience, and advanced SQL across large, complex datasets. Extensive experience with big data technologies and cloud data warehouses (Snowflake, BigQuery, Hadoop/Hive) at terabyte-and-growing scale.

Experience building reusable frameworks, platforms, or tooling that other engineers depend on (not just point solutions). Hands-on proficiency in both Python and Java for production systems. Systems performance and tuning expertise, with a clear understanding of how architectural decisions affect scalability and cost. Familiarity building REST services and working with event queue systems. Familiarity with Linux and cloud infrastructure design on AWS or equivalent cloud providers.

Comforta

Source listing: greenhouse_tripadvisor

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