Who we are
We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique perspective and experiences, so we can collectively revolutionize travel and together find the good out there.
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. Tripadvisor is extremely excited to play a pivotal role in supporting our travellers. With travel plans dashed in early 2020, many people have been dreaming about their next big holiday for more than a year, so it's no surprise that travellers are extra conscious of getting it just right when they do travel. Helping to play an important role in enabling travellers is an amazing opportunity over the next year and beyond.
Data engineering is one of the fastest growing engineering positions. Leading companies, such as Tripadvisor, are data driven, allowing us to quickly identify challenges, make timely decisions, and continue enhancing our user experience. Data engineering requires strong CS knowledge and analytical skills, the ability to learn new cutting edge technologies, and learning to master big data. Data engineers also need strong business knowledge and understanding of the data, and need to partner with the business to drive decisions. We are looking for strong engineers and analyst that want to become data engineers.
TripAdvisor provides a unique, global work environment that captures the speed, innovation and excitement of a startup, at a thriving, growing and well-established industry brand.
We take pride in our data engineering and are looking for a talented and highly-motivated engineer with a passion for solving interesting problems to add to our high-performing team.
What You Will Do
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 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 by creating efficient and scalable data models to be used across the organization.
Partnering with our analytics, data science, CRM, and machine learning teams.
Responsible for enterprise data integrity, validation, and documentation.
Solving data pipeline failure events and implementing sound anomaly detection
What We Seek
BS or MS in Computer Science or a related technical discipline
Ability to understand and develop ETL processes from concept to implementation
Intermediate proficiency in SQL query language.
Strong interest in manipulating, processing, and extracting data from large datasets
Familiarity or desire to learn technologies and tooling associated with databases and big data technologies
Big Data (i.e. Hadoop, Hive, BigQuery, Snowflake)
Relational DB (MS SQL, PostgreSQL/MySQL
Basic Understanding of data design and data modeling
Basic knowledge in functional programming in Python or in an equivalent language
Self-paced, proactive, and results-oriented person with a strong sense of ownership
Ability to communicate with both technical and non-technical staff.
Interest to work in a fast-paced and dynamic environment
Strong interpersonal skills, intense curiosity, and an enthusiasm for solving problems.
Nice to Have Skills:
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
Knowledge in programming languages such as Java or equivalent
What Do We Offer:
Highly competitive salary along with the following
Excellent contributory pension.
Full family private medical cover.
Full dental cover.
Annual wellbeing allowance (e.g. gym membership).
Personal travel reimbursement.
Critical illness plus full life cover.
Employee assistance program.