Hybrid Data Engineering Manager

at Lower

• Job title: Data Engineering Manager
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $125,000 - $185,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Cloud, ETL, Python, SQL
• Location requirements: Hybrid, Columbus, United States

About the role

• Engineering Manager leading and mentoring a team of data engineers at a fintech firm. Building scalable data pipelines and ensuring technical architecture aligns with business needs.

Responsibilities

• 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.
• 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.
• 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.
• 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.

Requirements

• 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.

Benefits

• 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