Data Engineering Lead

Job Title: Data Engineering Lead

Department: Technology

Report To: Chief Operating Officer

Salary Range: $125,000 - $140,000

**THIS IS AN IN-PERSON, IN-OFFICE ROLE**

**Recruiters are not welcome to contact*

Resolution Processing manages the non-legal and administrative aspects of the debt resolution process. We are a fast-paced and mission-driven organization within the debt resolution industry, committed to helping individuals navigate financial hardship with integrity and results.

We are seeking a highly skilled and experienced Data Engineering Lead to manage the development and optimization of our engineering team. You will play a critical role in building and leading a team of talented data engineers. This is a hands-on leadership position requiring technical expertise, excellent communication skills, and a strategic mindset.

Team Leadership

• Manage, mentor, and grow a team of data engineers
• Foster a collaborative, agile, and high-performance team culture
• Oversee sprint planning and code reviews

Data Infrastructure & Pipeline Development

• Design and implement scalable, efficient ETL/ELT pipelines
• Maintain CRM and real-time data processing systems
• Ensure high availability and reliability of data systems

Cross-Functional Collaboration

• Work closely with data scientists, analysts, and business stakeholders to understand data requirements
• Translate business needs into technical solutions that drive decision-making and business value
• Support analytics and ML/AI initiatives with reliable data delivery

Tooling & Innovation

• Evaluate and implement modern data engineering tools and platforms
• Promote continuous improvement in tooling, automation, and data processing capabilities
• Stay informed of industry trends and advocate for relevant adoption
  

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• 7 years of experience in data engineering or software engineering
• 3 years of experience in a leadership or team lead role
• Deep expertise in SQL, data modeling, and data warehouse design (e.g., Snowflake)
• Proficiency in Python for data processing
• Strong knowledge of cloud platforms (e.g., AWS)
• Solid understanding of version control (e.g., Git)
  

• Experience with real-time or streaming data architectures
• Familiarity with data cataloging, lineage, and metadata management tools
• Experience supporting data science or ML/AI pipelines