Senior Data Engineer

As a Senior Data Engineer at LendingTree, you'll be responsible for delivering innovative data integration solutions, creating real-time streaming data pipelines, and supporting Marketplace data integrations across our various business lines. You'll work collaboratively with engineers, data architects, and product owners while also developing and managing technical documentation to ensure its accessibility.

To qualify for the Senior Data Engineer position at LendingTree, candidates should have at least 3 years of experience with data services using cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with event streaming technologies, data warehousing, and orchestration tools, as well as strong SQL skills and proficiency in a programming language such as Python or Java, are also key.

Yes, the Senior Data Engineer role at LendingTree requires in-person attendance in the Charlotte, NC office for at least 3 days a week, ideally from Tuesday to Thursday. This allows for effective collaboration within the team and across departments.

The culture at LendingTree is fast-paced and entrepreneurial. As a Senior Data Engineer, you'll be encouraged to be collaborative, ambitious, and candid. We value hard work and innovation, with a strong focus on testing and improving our products while enjoying a relaxed atmosphere with flexible work options.

Senior Data Engineers at LendingTree can enjoy a range of benefits, including competitive medical, dental, and vision insurance, a 401(k) matching plan, flexible PTO policies, and access to an onsite gym. Our environment promotes a good work-life balance and recognizes efforts with incentive compensation.

When answering this question, highlight specific projects where you've implemented AWS services and the impact it had. Discuss your experience with services like S3 for storage, Lambda for serverless architecture, or RDS for databases.

Describe your familiarity with technologies such as Kafka, AWS Kinesis, or Google Pub/Sub. Provide examples of how you've designed and implemented streaming data pipelines and the business needs they addressed.

Outline your process for designing real-time data pipelines, emphasizing the tools used, the data sources you integrated, and the importance of scalability. Include specific examples demonstrating your problem-solving skills.

Mention the specific data warehousing solutions you've worked with, the types of data you've managed, and how you optimized queries or improved performance. Focus on tangible outcomes from your efforts.

Explain the importance of documentation in your role. Describe your preferred documentation tools and methods to ensure clarity and accessibility. Share your approach to keeping documentation up to date throughout the project lifecycle.

Discuss your experience with testing and validation of data solutions. Highlight any methodologies or frameworks you use to ensure quality, such as continuous integration/testing practices, and provide examples of how this process benefited your past projects.

Share a detailed example of a challenging project, focusing on the complexity of data integration, the steps you took to overcome obstacles, and the positive outcomes. This highlights your critical thinking and problem-solving abilities.

Describe your comfort levels with different programming languages, particularly Python, Java, or Scala. Share your reasoning for preferences based on performance, project requirements, or personal experience.

Discuss your methods for staying informed, such as following industry blogs, participating in forums, attending webinars, or taking courses. Emphasize your commitment to continual learning and how it influences your work.

Provide a specific example where you successfully conveyed intricate data information to non-technical audiences. Highlight the approach you took to simplify the concepts and the positive results of that communication.