Data Engineer II

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.

About the Data Platform Team

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 software and infrastructure that enable Tripadvisor to better understand visitor preferences, power experimentation across all surfaces (website, mobile app, and customer communications), and drive GenAI, Analytical, and DSML initiatives at petabyte scale. Our team builds and maintains:

• 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

We collaborate closely with Product, Analytics, Data Science, CRM, Marketing, Finance, and Machine Learning teams across Tripadvisor’s global engineering organization.

Tripadvisor is looking for a Data Engineer II 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 bring both strong software engineering fundamentals and hands-on data engineering expertise — writing production-quality Java and Python, 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.

What You’ll Do

Data Engineering & Data Products, ETLs

• Design, build, and maintain robust ETL/ELT data pipelines that process terabyte-scale data across Snowflake, BigQuery, Hive, and other platforms.

• Develop scalable, reusable data models and curated data sets for analytics, data science, CRM, machine learning, and other data consumers across the organization.

• Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection.

• Ensure enterprise data integrity, validation, documentation, and governance.

Platform & Software Engineering

• Write production Java and Python code across our evolving platform stack — from data ingestion and event processing to REST services and internal tooling.

• Build and maintain 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).

• Operate on and improve cloud infrastructure on AWS, with familiarity with Gradle, Linux, and related tooling.

Quality, Collaboration & Ownership

• Take on projects with independence and a mandate to leave things better than you found them.

• Be integral to code quality on your team through leadership in design and code review.

• Collaborate closely with Product, Design, Analytics, and Data Science teams to define specifications and deliver high-quality solutions.

• Communicate effectively with both technical and business stakeholders; translate complex data problems into clear solutions.

• Work alongside engineering groups located around the world in a fast-paced, dynamic environment.

Skills & Experience

Required

• 4–5+ years of data engineering or general software development experience in a commercial setting.

• Strong hands-on proficiency in both Java and Python for production systems.

• Demonstrated experience designing and implementing complex ETL/ELT processes from concept to production.

• Proficiency in SQL and data exploration across large, complex datasets.

• Experience with big data technologies (Hadoop, Hive, BigQuery, Snowflake) and working with terabyte-scale or larger datasets.

• Solid foundation in data structures, algorithms, and object-oriented design.

• Professional experience building REST services and working with event queue systems.

• Familiarity with Linux and cloud infrastructure design on AWS or equivalent cloud providers.

• Systems performance and tuning experience, with an understanding of how architecture impacts scalability.

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

• Strong analytical skills; desire to write clean, correct, and efficient code.

• Self-paced, organized, and detail-oriented with a strong sense of ownership, urgency, and pride in your work.

• Ability to break down complex problems into simple, pragmatic solutions.

• Strong interpersonal skills, intense curiosity, and enthusiasm for solving difficult problems.

• Willingness and ability to take on new technologies as our stack evolves.

Nice to Have

• Experience with stream processing frameworks such as Flink or Spark Streaming.

• Experience with task orchestration tools such as Apache Airflow or similar systems.

• Familiarity with additional technologies: GraphQL, React, HTML5, JavaScript, CSS, Postgres, Gradle, BERT.

• Experience working with and designing infrastructures for large-scale data processing (Hive, Snowflake, NoSQL databases).

• Experience with data governance practices and tooling.

• Exposure to and/or interest in machine learning, data science, or GenAI to help solve engineering challenges innovatively.

• Experience developing scalable code for high-volume, low-latency systems.

We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at  View email address on job-boards.greenhouse.io .

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