Data Engineer

• Build and operate scalable batch and real-time streaming pipelines, ETL/ELT workflows, and database applications across multiple lines of business, with clear plans for schema changes, retries, and recovery.
• Design dimensional models and reusable datasets for business, analytics, and data science needs. Perform complex data analysis to validate business rules, identify trends and anomalies, and uncover opportunities.
• Own the reliability and efficiency of your data solutions: automate quality checks, monitor freshness, tune performance and compute costs, and participate in the on-call rotation to resolve incidents and prevent recurrence.
• Create reusable frameworks and development patterns that improve delivery speed and consistency. Apply automated testing, code review, and repeatable deployments; maintain 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. Validate generated code and results, protect sensitive data, and assess whether these tools improve quality and reduce delivery time.

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 turn business priorities into practical data solutions., * 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 produce measurable reductions in runtime, compute cost, or recurring incidents.
• Reusable frameworks, useful documentation, and validated AI workflows shorten delivery time while maintaining quality.

Life at LendingTree

We’re a collaborative, entrepreneurial team that’s curious, creative, and always ready to roll up our sleeves and get things done. You’ll work alongside smart, driven people who care about doing great work - and about helping each other succeed.

We believe the best ideas come from different perspectives, and we’re committed to creating a workplace where people feel welcomed, valued, and empowered to make an impact. You’ll have the trust and flexibility to do your best work, the opportunity to take ownership and try new things, and teammates who genuinely enjoy working together.

And while we work hard, we don’t take ourselves too seriously. We celebrate wins, recognize great work (our GSD - Get Stuff Done - Award is a fan favorite), and make time to have some fun along the way.

• 5+ years of hands-on experience in data engineering, 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 an understanding of batch and streaming integration patterns.
• Strong dimensional modeling skills and sound data warehousing practices, including defining grain, fact and dimension tables, and how historical changes are represented.
• Ability to deliver projects with minimal guidance in an Agile team, using testing, version control, documentation, and systematic troubleshooting to build maintainable solutions.
• Clear written, verbal, and data presentation skills, including the ability to understand business needs and explain findings and technical decisions through documentation, presentations, or dashboards.

What Will Help You Thrive You’re curious about the business behind the data, learn new tools thoughtfully, communicate issues early, and share both credit and lessons learned. Experience in any of the following is a plus:

• 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.
• using 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.

Build and operate batch and streaming data pipelines, ETL/ELT workflows, data warehouses, dimensional models, and reusable data services. Improve reliability, performance, quality, and cost efficiency through monitoring, testing, automation, and incident response. Partner with analytics, data science, product, business, platform, and infrastructure teams to deliver production data solutions and roadmap initiatives. Apply AI-assisted tools responsibly to development, testing, documentation, and troubleshooting. The summary above was generated by AI, We want you to feel supported at work and beyond. Our benefits and programs are designed to help you stay healthy, recharge, plan for the future, and bring your best to whatever matters most to you.

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

Base Pay:

The base pay range for this position is $100,000-130,000; pay offered may vary based on location, internal factors, job-related knowledge, skills, and experience.