TripAdvisor
Our data engineering team is focused on delivering Tripadvisor's first-in-class data products that serve all data users across the organization. As a member of the Data Platform Enterprise Services Team, you will collaborate with engineering and business stakeholders to build, optimize, maintain, and secure the full data vertical including tracking instrumentation, information architecture, ETL pipelines, and tooling that provide key analytics insights for business-critical decisions at the highest levels of Product, Finance, Sales, CRM, Marketing, Data Science, and more. All in a dynamic environment of continuously modernizing tech stack including highly scalable architecture, cloud-based infrastructure, and real-time responsiveness. 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. Responsibilities: Providing the organization's data consumers with 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. Requirements: BS or MS degree in Computer Science or a related technical discipline. 4+ years of data engineering or general software development experience. Experience with Big Data technologies such as Snowflake, Databricks, and BigQuery. Demonstrated proficiency in data design and data modeling. Experience in developing complex ETL processes from concept to implementation to deployment and operations, including SLA definition, performance measurements, and monitoring. Proficiency in writing and optimizing SQL queries; data exploration skills with a proven record of querying and analyzing large datasets. Hands-on knowledge of the AWS ecosystem, including storage (S3) and compute (EKS, ECS, Fargate) services. Experience with relational databases such as Postgres, and with programming languages such as Python and/or Java. Knowledge of cloud data warehouse concepts. Organized and detail-oriented person with a strong sense of ownership. Ability to work in a fast-paced and dynamic environment. Strong verbal and written communication skills. Ability to effectively communicate with both business and technical teams. Ability to make progress on projects independently, intense curiosity, and enthusiasm for solving difficult problems. #J-18808-Ljbffr