Senior Data Engineer

LendingTree’s Data Engineering team helps power reporting, analytics, and data science across lending and insurance. In this onsite Senior Data Engineer role in Seattle, you’ll build pipelines, models, and data services that prioritize reliability, efficiency, and delivery consistency. You’ll work across batch and streaming ETL/ELT, dimensional modeling, production operations, and practical AI-assisted development, using tools that support faster development while keeping code and results validated.

Responsibilities

• Build and operate scalable batch and real-time streaming pipelines, ETL/ELT workflows, and database applications across multiple lines of business, with 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, spot trends and anomalies, and identify opportunities.
• Own the reliability and efficiency of data solutions by automating quality checks, monitoring data 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, covering platform capabilities, priorities, technical trade-offs, and delivery estimates.
• Use AI tools for development, testing, documentation, and troubleshooting, including validation of generated code and results, protecting sensitive data, and assessing whether AI improves quality and reduces delivery time.

Requirements

• 5+ years of hands-on data engineering experience, including data warehousing, ETL/ELT development, and analytics, with a track record of delivering and supporting production solutions.
• Advanced SQL skills: writing, tuning, and debugging complex queries, plus data analysis to investigate issues.
• Experience designing data lakes and warehouses on scalable, distributed platforms, with an understanding of batch and streaming integration patterns.
• Strong dimensional modeling and data warehousing practices, including defining grain, 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 to build maintainable solutions.
• Strong written, verbal, and data presentation skills, including understanding business needs and explaining 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, Claude Code, Codex, Cursor, Maia, CI/CD

Compensation and Authorization

Base pay: USD 100,000 - 130,000 per year. Pay offered may vary based on location, internal factors, job-related knowledge, skills, and experience.

Incentive compensation: Eligible for an annual performance bonus.

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.

Benefits

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

What Will Help You Thrive

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

Who You’ll Work With

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

What Success Looks Like

• 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.