About the company
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.
Tripadvisor, the world’s largest travel site, operates at scale with over 500 million reviews, opinions, photos, and videos reaching over 390 million unique visitors each month. We are a data driven company that leverages our data to empower our decisions.
Responsibilities
- Providing the organization’s data consumers high quality data sets by data curation, consolidation, and manipulation from a wide variety of large scale (terabyte and growing) sources.
- Building high quality data pipelines and ETL processes that interact with terabytes of data on leading platforms such as Snowflake and BigQuery.
- Developing and improving our enterprise data marts by creating efficient and scalable data models to be used across the organization.
- Partnering with our analytics, data science, crm, and machine learning teams for data solutions.
- Responsible for an enterprise data mart integrity, validation, and documentation.
- Responsible for the data pipelines’ SLA and dependency management.
- Writing technical documentation for data solutions, and presenting at design reviews.
- Solving data pipeline failure events and implementing sound anomaly detection.
- Working with various teams from analytics to product owners and front end developers on tracking solutions and solving technical challenges.
- Leading medium to large size projects in terms of writing technical specs and project planning.
- Mentoring junior members of the team.
Requirements
- BS or MS degree in Computer Science or a related technical discipline.
- 6+ years of data engineering or general software development experience.
- Experience working with large datasets (terabyte scale and growing) and familiarity with various technologies and tooling associated with databases and big data: Big Data (i.e. Hadoop, Hive, BigQuery, Snowflake), Relational DB (MS SQL, PostgreSQL/MySQL).
- Comprehensive data design and data modeling experience.
- Solid experience developing complex ETL processes from concept to implementation; these should include defining SLA, performance measurements and monitoring.
- Advanced query language and data exploration skills, proven record of writing complex SQL queries across large datasets.
- Systems performance and optimization experience, with an eye for how systems architecture and design impacts performance and scalability.
- Experience in functional programming in Python or in an equivalent language.
- Strong software engineering principles.
- Self-paced, organized, and detail-oriented person with a strong sense of ownership.
- Strong communication skills to effectively communicate with both business and technical teams.
- Ability to work in a fast-paced and dynamic environment.
- Proven record of technical leadership on planning and driving medium to large size projects and handling challenging deadlines.
- Strong interpersonal skills, intense curiosity, and an enthusiasm for solving difficult problems.
- Ability to break down complex problems into simple solutions.
- Ability to work with end users to solve technical challenges.
- Comfortable owning the full data vertical and work autonomously.
- Ability to mentor and support more junior members of the Team.
- Nice to have: Exposure to and/or interest in machine learning and data science specifically to help solve day-to-day problems and reach objectives in an innovative way; Experience working with task orchestration tools, Airflow or similar systems; Comfortable working in a Linux CLI environment; Experience in designing high-scale, fault-tolerant and performant distributed applications; Experience in developing and managing real-time data pipelines.