Senior Data Engineer

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. 

• 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.