Data Engineer III

Expedia•Austin, TX

1d•$146,000 - $204,500

About The Position

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business. Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere. Role Summary A high performing individual contributor who mentors junior engineers. applies new data engineering principles to improve existing systems, and leads complex, well-defined projects.

Requirements

Experience 5+ years for Bachelor's 3+ years for Master's
Software development in at least 3 different languages.
Built and maintained more than one data pipeline/data product in production environments (bug fixing, troubleshooting, monitoring, etc.).
Bachelor's or Master's or equivalent experience.
Displays strength in a couple of programming languages relevant to data (e.g. Java, Spark, Python).
Identifies strengths and weaknesses among languages for particular use cases.
Applies organizational technology patterns effectively in their projects and makes recommendations on alternate options.
Has hands-on experience working with large volumes of data including different patterns of data ingestion, processing (batch & real-time), movement, storage and access (for both internal and external to BU) and is able to make independent decisions within scope of project.
Displays a good understanding of data structures and algorithms.
Has hands-on experience working with at least 1 cloud technology and its offerings within the data specialization.
Understands how projects/teams interact with other teams.
Understands and design moderately complex systems.
Has some familiarity with some data modeling and schema design patterns.
Has a good understanding of organizational reference patterns and technology choices and applies them to their projects.
Tests and monitors code at the project level.
Understands how to test and monitor tools.
Debugs applications.
Tests, debugs and fixes issues within established SLAs.
Designs software that is easily testable and observable.
Understands how team's goals fit a business need.
Identifies business problems at the project level and provide solutions.
Development/language skills (Java/Python/Scala)
Architecture
Testing, monitoring, alerting
Business acumen/domain knowledge
Data access patterns
Streaming technology
Data validation
Data performance
Cost optimization

Responsibilities

Mentors junior engineers.
Applies new data engineering principles to improve existing systems.
Leads complex, well-defined projects.
Develops and tests complex or non-routine software applications and related programs and procedures to ensure they meet design requirements.
Effectively applies knowledge of software design principles, data structures and/or design patterns and computer science fundamentals to write code that is clean, main table, optimized, modular with good naming conventions.
Effectively applies knowledge of databases and database design principles to solve data requirements.
Effectively applies concepts of object oriented design, distributed computing, performance/scalability tuning, advanced data structures and algorithms to batch and real-time stream analytics and large data processing.
Understands software frameworks and how to leverage them to write simpler code.
Leads and clarifies code evolution in code reviews.
Coordinates different stakeholders with varied perspectives to develop solutions to issues, and contributes own suggestions.
Thinks holistically to identify opportunities around policies/ processes to increase efficiency across organizational boundaries.
Assists with a whole systems approach to analyzing issues by ensuring all components (structure, people, process and technology) are identified and accounted for.
Recognizes areas of inefficiency in code or systems operation and offer suggestions for improvements.
Recommends advancements, innovations and changes in technologies (specifically relating to data engineering, cloud data platforms, data models, enterprise information management, business intelligence and data science).
Compiles data and reports on major operational or technical initiatives (like RCAs) to larger groups, whether via written or oral means.