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Lower

Data Engineering Manager

Sorry, this job was removed at 08:54 a.m. (CST) on Tuesday, Mar 31, 2026
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In-Office
Austin, TX, USA
In-Office
Austin, TX, USA

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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:

The Engineering Manager will lead and grow a high-impact team of data engineers while remaining hands-on in the codebase. This role blends people leadership, technical execution, and architectural stewardship. The Engineering Manager is responsible for guiding a team of three data engineers, setting technical direction, planning and prioritizing work, and contributing directly through individual contributor efforts. 

This is an ideal opportunity for a senior engineer or manager who enjoys mentoring others, improving systems, and still spending meaningful time building pipelines, reviewing code, and solving complex data problems. The role plays a critical part in shaping the future of our data platform as we scale, modernize, and deepen our impact across the business. 


Location: Columbus, OH or Austin, TX required with weekly in-office expectations.
Compensation: Compensation for this role varies based on location and experience level. The anticipated base salary ranges are:
  • Columbus, OH: $125,000–$169,000
  • Austin, TX: $135,000–$185,000
What you'll do:Team Leadership & Management 
  • Manage, mentor, and support a team of data engineers, fostering growth, accountability, and strong engineering practices. 
  • Plan, prioritize, and groom team work through sprint planning, backlog refinement, and capacity management. 
  • Conduct regular 1:1s, provide feedback and coaching, and support career development for team members. 
  • Partner with cross-functional leaders to align engineering priorities with business needs. 
Hands-On Technical Contribution 
  • Act as a player-coach by owning and delivering individual contributor work alongside the team. 
  • Design, build, and maintain scalable data pipelines using tools such as Snowflake, Fivetran, SQL, Python, and custom API integrations. 
  • Review pull requests, enforce coding standards, and ensure high-quality, maintainable, and well-documented code. 
  • Troubleshoot and resolve data pipeline issues, performance bottlenecks, and reliability concerns. 
Architecture & Platform Ownership 
  • Own and evolve the data engineering architecture with a focus on scalability, reliability, and simplicity. 
  • Identify and reduce technical debt, improve repository structure, and introduce best practices across the codebase. 
  • Partner closely with the analyst side of the team to ensure datasets are well-modeled, performant, and analysis-ready. 
  • Contribute to tooling, process improvements, and documentation that increase team velocity and data quality. 
Stakeholder Collaboration 
  • Work directly with analyst teammates, product, marketing, and business stakeholders to understand data needs and translate them into technical solutions. 
  • Provide technical guidance and context to non-technical partners. 
  • Proactively identify opportunities where data engineering can unlock new insights or efficiencies. 
Who you are:
  • Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience). 
  • 6+ years of experience in data engineering, analytics engineering, or related roles. 
  • Strong hands-on experience with cloud data warehouses (Snowflake or equivalent).
  • Expert-level SQL skills, including query optimization and analytical data modeling.
  • Strong Python experience for data pipeline development, automation, and orchestration.
  • Experience implementing ELT/ETL workflows using managed tools (e.g., Fivetran) and custom API-based ingestion solutions.
  • Solid understanding of data modeling, pipeline orchestration, and analytics enablement. 
  • Experience reviewing code, improving architecture, and managing technical debt. 
  • Strong communication skills and ability to balance technical depth with business context. 
Preferred Experience 
  • Prior experience leading or mentoring engineers (formal management experience preferred but not required). 
  • Mortgage, real estate, or financial services industry experience is a strong plus. 
Technical Environment & Stack 
  • Programming: Python, SQL, Bash scripting. 
  • Cloud: AWS (Lambda, S3, API Gateway, CloudWatch, IAM). 
  • Data Warehouse: Snowflake, dimensional modeling, query optimization. 
  • ETL/ELT: dbt, pandas, custom Python workflows. 
  • DevOps: GitHub Actions, Docker, automated testing. 
  • APIs: REST integration, authentication, error handling. 
  • Data Formats: JSON, CSV, Parquet, Avro. 
  • Version Control: Git, GitHub workflows. 
What you'll get:
  • Extended benefit offerings including medical/dental/vision, parental leave, life insurance, short- and long-term disability
  • Paid holidays and paid time off
  • 401K with company match
  • Discount on home mortgage refinances or purchase

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