Senior Data Engineer

LendingTree is hiring a Senior Data Engineer in Seattle, WA (onsite) to build scalable batch and real-time data pipelines, dimensional models, and reliable data services. This role supports reporting, analytics, and data science across lending and insurance while emphasizing operational excellence and practical AI-assisted development.

Key Responsibilities

• Build and operate scalable batch and real-time streaming pipelines, ETL/ELT workflows, and database applications across multiple lines of business, including plans for schema changes, retries, and recovery.
• Design dimensional models and reusable datasets for business, analytics, and data science; perform complex data analysis to validate business rules, identify trends and anomalies, and uncover opportunities.
• Own reliability and efficiency by automating quality checks, monitoring freshness, tuning performance and compute costs, and participating in an on-call rotation to resolve incidents and prevent recurrence.
• Create reusable frameworks and development patterns that improve delivery speed and consistency, including automated testing, code review, repeatable deployments, and maintaining technical standards, runbooks, and learning materials.
• Partner with business users and engineering teams to clarify requirements, resolve issues, and contribute to the data engineering roadmap, including platform capabilities, priorities, technical trade-offs, and delivery estimates.
• Apply AI tools to development, testing, documentation, and troubleshooting, while validating generated code and results, protecting sensitive data, and assessing whether tools improve quality and reduce delivery time.

Required Qualifications

• 5+ years of hands-on data engineering experience, including data warehousing, ETL/ELT development, and analytics, with a record of delivering and supporting production solutions.
• Advanced SQL skills, including writing, tuning, and debugging complex queries, and using data analysis to investigate problems.
• Experience designing data lakes and warehouses on scalable, distributed platforms, with understanding of batch and streaming integration patterns.
• Strong dimensional modeling skills and sound data warehousing practices, including grain definition, fact and dimension tables, and representing historical changes.
• Ability to deliver projects with minimal guidance in an Agile team, using testing, version control, documentation, and systematic troubleshooting.
• Strong written, verbal, and data presentation skills, including the ability to understand business needs and explain findings and technical decisions through documentation, presentations, or dashboards.

Technologies

• SQL, Snowflake, Streams and Tasks, SQL Server, Matillion, dbt, Python, C#, PowerShell
• Git, GitLab, Power BI, Tableau, Streamlit
• AI-assisted development tools: Claude Code, Codex, Cursor, Maia
• CI/CD

Compensation and Performance Bonus

• Base pay range: USD 100,000 - 130,000 per year
• Annual performance bonus eligibility: Yes (incentive compensation)
• Pay note: Pay offered may vary based on location, internal factors, job-related knowledge, skills, and experience.

Benefits

• Medical, dental, and vision insurance
• 401(k) matching
• Generous time off
• Wellness programs and resources
• Annual performance bonus eligibility

Work Authorization

This role is not eligible for immigration sponsorship. Please do not apply if you will need employer sponsorship now or in the future to begin or continue employment.

What Will Help You Thrive

• Experience with Snowflake virtual warehouses, performance and cost tuning, Streams and Tasks, and/or SQL Server
• Experience with Matillion, dbt, or similar tools for data integration and transformation
• Experience with Python, C#, or PowerShell for integration and automation; proficiency with Git/GitLab for collaboration and CI/CD workflows
• Experience with Power BI, Tableau, or Streamlit for dashboards, data applications, and communicating insights
• Ability to use AI-assisted development tools such as Claude Code, Codex, Cursor, or Maia to accelerate coding, testing, documentation, and troubleshooting while validating generated code and results
• S. in Computer Science, Mathematics, or a related field, or equivalent practical experience

Success Measures

• Production pipelines meet agreed freshness and reliability targets with clear monitoring, ownership, and recovery procedures.
• Business, analytics, and data science partners use tested models with consistent definitions and less manual reconciliation.
• Query tuning and pipeline improvements lead to measurable reductions in runtime, compute cost, or recurring incidents.
• Reusable frameworks, useful documentation, and validated AI workflows shorten delivery time while maintaining quality.

Team and Collaboration

You will join the Data Engineering team and work with your manager, fellow engineers, and partners in analytics, data science, product, and business operations across Lending and Insurance. You will also collaborate with platform and infrastructure teams to manage dependencies, support production services, and translate business priorities into practical data solutions.