Senior Data Engineer

Lower, LLC; Columbus (OH); On-site; USD 80,000 - 110,000; Full time

Job summary

Lower, LLC in Columbus, Ohio, is seeking a Data Engineer II to enhance data pipelines and support analytics. This role offers a chance to work with cutting-edge technologies in a cohesive team environment focused on driving the mission of making homeownership accessible.

Ideal candidates should have experience with SQL and cloud data tools, a collaborative mindset, and a passion for using AI tools to enhance workflows. Join a leader in fintech committed to innovation and excellence.

Qualifications

• 3–5+ years of experience in data engineering or a similar role.
• Strong skills in SQL and experience handling large datasets.
• Familiarity with cloud data platforms like Snowflake and Redshift.

Responsibilities

• Build and optimize data pipelines across various systems.
• Support and enhance data warehouse infrastructure.
• Collaborate with cross-functional teams to support BI workflows.

Skills

SQL

Python

Data Pipeline Maintenance

Data Warehousing

AI Tools

Tools

Snowflake

dbt

Looker

Domo

Job description

Job Overview

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. Our people are what sets us apart. Join us and be part of something bigger.

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.

Responsibilities

• 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.

Qualifications

• 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

• Experience in the mortgage, lending, financial services, real estate, or fintech industries.
• Hands‑on experience with Snowflake, dbt, Looker, and/or Domo.
• Experience using AI‑assisted development tools such as Claude Code, Cursor, GitHub Copilot, or similar tools.
• Experience exploring or building with AI agents, workflow automation, LLM‑powered internal tools, or agentic development frameworks.
• Experience with orchestration tools, cloud platforms, CI/CD workflows, or modern data stack tooling.
• Familiarity with data governance, data quality testing, observability, and documentation best practices.
• Experience supporting executive reporting, operational analytics, marketing analytics, mortgage operations, or sales funnel reporting.

Lower provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.