[All remote jobs](https://jobicy.com/jobs.md)[![LendingTree logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2022/03/a087cb002c7df273f6942219c6d4ae5e.jpeg)](https://jobicy.com/company/lendingtree.md)[LendingTree](https://jobicy.com/company/lendingtree.md) # Senior Data Engineer AI Summary LendingTree is seeking a Senior Data Engineer to build and operate batch and real-time data pipelines, ETL/ELT workflows, warehouse models, and production data services. The role focuses on data reliability, freshness monitoring, recovery procedures, performance tuning, and cloud-compute cost efficiency across lending and insurance products. The engineer will partner with analytics, data science, product, platform, and business teams while contributing to roadmap decisions and reusable engineering standards. Core requirements include advanced SQL, dimensional modeling, data warehousing, distributed data platforms, Agile delivery, and independent ownership of production systems. Experience with Snowflake, dbt or Matillion, Python, CI/CD, BI tools, and validated AI-assisted development is advantageous.[Apply for this job](#job-application)[View company](https://jobicy.com/company/lendingtree.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 100k–130k / yrDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceSeniorPublished8 Nov 2026Apply before8 Dec 2026Listing views49Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. Candidates must be legally authorized to work in the United States. [LendingTree](https://jobicy.com/company/lendingtree.md) and its affiliates (“LendingTree”) will not provide or assume sponsorship for employment visas for this position, now or in the future. The Opportunity As a Data Engineer at LendingTree, you’ll build the pipelines, models, and data services behind reporting, analytics, and data science across our lending and insurance businesses. You’ll tackle complex integration and modeling challenges, improve reliability and cost efficiency, and apply practical AI tools to help the team deliver better data solutions faster. How You’ll Make an Impact * 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. What You’ll Bring * 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. 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 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. Come grow with us, make an impact, and help us build what’s next. What We Offer 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. Incentive Compensation: This position is eligible for an annual performance bonus. Work Authorization: This role is not eligible for immigration sponsorship. Please do not apply for this role if you will need employer sponsorship now or in the future to begin or continue employment. Everyone Belongs Here LendingTree is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion (or creed), gender, gender expression, age, national origin, disability, marital status, sexual orientation, or military status. If you believe you need a reasonable accommodation in order to search for a job opening or to submit an application, please email us at [humanresources@lendingtree.com](mailto:humanresources@lendingtree.com). [CCPA Disclosure](https://www.lendingtree.com/legal/privacy-notice-for-lendingtree-job-applicants-and-employees-who-are-california-residents/) Show more [Apply now >](https://jobicy.com/jobs/159828-senior-data-engineer-9.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightЭто senior-роль с ответственностью за надёжные production-пайплайны, потоковую обработку, моделирование данных и участие в on-call. Кандидат должен самостоятельно принимать технические решения и объяснять их как инженерам, так и бизнес-партнёрам. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$115,000US market range (per year)$105k–$145k0$159.50k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. Работодатель указывает базовую оплату $100,000–$130,000 USD. Годовой период для базовой зарплаты логически выведен из размера диапазона, американского рынка и senior-уровня роли, поскольку период прямо не указан. Оценочный рыночный диапазон для Senior Data Engineer в США составляет $105,000–$145,000 USD в год; годовой бонус не включён в базовую зарплату. ## Core skills Skills and capabilities most closely associated with this opportunity. [Data Engineering](https://jobicy.com/jobs?search_keywords=Data%20Engineering.md)[Advanced SQL](https://jobicy.com/jobs?search_keywords=Advanced%20SQL.md)[ETL/ELT](https://jobicy.com/jobs?search_keywords=ETLELT.md)[Data Warehousing](https://jobicy.com/jobs?search_keywords=Data%20Warehousing.md)[Dimensional Modeling](https://jobicy.com/jobs?search_keywords=Dimensional%20Modeling.md)[Data Pipelines](https://jobicy.com/jobs?search_keywords=Data%20Pipelines.md)[Streaming Data](https://jobicy.com/jobs?search_keywords=Streaming%20Data.md)[Snowflake](https://jobicy.com/jobs?search_keywords=Snowflake.md)[dbt](https://jobicy.com/jobs?search_keywords=dbt.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[Data Quality](https://jobicy.com/jobs?search_keywords=Data%20Quality.md)[Performance Tuning](https://jobicy.com/jobs?search_keywords=Performance%20Tuning.md)[CI/CD](https://jobicy.com/jobs?search_keywords=CICD.md)[Git](https://jobicy.com/jobs?search_keywords=Git.md)[Power BI](https://jobicy.com/jobs?search_keywords=Power%20BI.md) Sample interview questionsHow would you design a reliable pipeline that ingests both batch and real-time lending data?I would separate ingestion, transformation, and serving layers, define schemas and data contracts, and use idempotent processing with checkpoints for streaming workloads. I would add retry policies, dead-letter handling, freshness monitoring, and documented recovery procedures so failures can be detected and resolved safely. How do you approach dimensional modeling for analytics users? I begin by defining the business process and the grain of each fact table, then identify conformed dimensions and the measures users need. I document business definitions, select an appropriate strategy for slowly changing dimensions, and validate the model with stakeholders before productionizing it. Describe how you would investigate an unexpectedly slow Snowflake transformation. I would review query profiles, warehouse size and utilization, data scanned, joins, pruning, skew, and repeated transformations. I would then test targeted improvements such as query rewrites, incremental processing, clustering where justified, or task scheduling changes, measuring both runtime and cost before deployment. What practices do you use to maintain data quality in production? I implement automated tests for schema, uniqueness, referential integrity, accepted values, volume changes, and freshness. I also establish observability dashboards and alert thresholds, assign dataset ownership, and create runbooks so incidents are resolved consistently and their root causes are addressed. How do you use AI-assisted development tools responsibly in data engineering? I use them to accelerate drafting code, tests, documentation, and troubleshooting hypotheses, but I validate every output through code review, testing, and data-quality checks. I avoid exposing sensitive data to unapproved tools and ensure generated solutions meet security, performance, and maintainability standards. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. 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