Build, maintain , and optimize data pipelines across a variety of source systems.
Support and improve our core data warehouse infrastructure, primarily in Snowflake , with some legacy warehouse environments such as Redshift .
Develop and maintain transformation logic, models, and reusable data assets using tools such as dbt .
Build new warehouse functionality, curated data models, marts, and tables that support reporting, analytics, operations, and stakeholder decision-making.
Support BI and reporting workflows across Looker and Domo , partnering with analysts and business teams to ensure trusted, consistent metrics.
Manage and troubleshoot existing data pipelines, jobs, connectors, data shares, SFTP connections, APIs, and native integrations.
Write and maintain production-quality SQL, Python scripts, and transformation workflows.
Partner with analysts and business stakeholders to understand data needs and translate them into reliable, scalable data solutions.
Help ensure our data is accurate , timely , well-documented, and trusted by the teams that rely on it.
Explore and adopt AI-assisted engineering tools such as Claude Code, Cursor, and other agentic AI frameworks to improve development velocity, documentation, testing, data quality, and operational efficiency.
Support warehouse migrations, platform consolidation, and modernization efforts as the company continues to scale.
Collaborate with cross-functional teams across marketing, sales, operations, finance, product, technology, and mortgage operations.
Contribute to data quality monitoring, observability, governance, and process improvements.
Requirements
3-5+ years of professional experience in data engineering, analytics engineering, business intelligence engineering, or a similar data-focused role.
Strong SQL skills and experience working with large, complex datasets.
Experience building and maintaining production data pipelines.
Experience with cloud data warehouses such as Snowflake , Redshift , BigQuery , or similar platforms.
Experience with dbt or similar data transformation frameworks.
Experience with Python or another scripting language used for data processing, automation, or pipeline orchestration.
Familiarity with data integration patterns, including APIs, SFTP transfers, file-based ingestion, third-party connectors, data shares, and native platform integrations.
Comfort working with BI and analytics tools such as Looker, Domo, Tableau, Power BI , or similar platforms.
Interest in using modern AI tools to improve data engineering workflows, including AI-assisted coding, documentation, testing, code review, and automation.
Comfort working with messy, real-world business data and turning it into clean, trustworthy, usable data assets.
Strong problem-solving skills and attention to detail.
Ability to work with both technical and non-technical stakeholders.
A collaborative mindset and a desire to build reliable systems that help the broader company succeed.
Preferred Experience
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Additional Information
Here at Lower , we believe homeownership is the key to building wealth , and we're making it easier and more accessible than ever. As a mission-driven fintech , we simplify the home-buying process through cutting-edge technology and a seamless customer experience .
With tens of billions in funded home loans and top ratings on Trustpilot (4.8), Google (4.9), and Zillow (4.9) , we're a leader in the industry. But what truly sets us apart? Our people. Join us and be part of something bigger.
Job Description:
Lower.com is looking for a Data Engineer II to join our Data & Analytics team. This is an exciting opportunity to work on a team that supports stakeholders across the entire company and has access to the full breadth of Lower's data ecosystem.
As a Data Engineer, you will help build, maintain , and improve the data infrastructure that powers reporting, analytics, operations, marketing, finance, product, and executive decision-making across the business. You will work closely with analysts, data engineers, business leaders, and technical stakeholders to create reliable data pipelines, maintain and enhance our data warehouse, and build scalable data products that help the company move faster and make better decisions.
Our current stack includes Snowflake, dbt , Looker, Domo , and a variety of source-system connectors, native pipelines, APIs, data shares, SFTP-based integrations, and Python-based workflows. We are also actively exploring how modern AI development tools and agentic workflows - including tools like Claude Code, Cursor, AI-assisted development, and data-focused automation frameworks - can help us build faster, improve quality, and create better internal data products.
This is a great role for someone who enjoys working in a dynamic, high-growth environment, likes solving data problems, and is excited by the opportunity to use modern tooling, including AI-assisted development, to improve how data teams work.
Lower · Columbus