Lead Data Engineer

Team: IT

Location: US

Commitment: Full-time

Workplace Type: remote

Accountabilities

• Lead, mentor, and develop the Data Engineering team, setting clear expectations for performance, quality, accountability, and ownership.

• Manage team priorities, workload, and delivery plans in alignment with organizational objectives and the broader data roadmap.

• Provide technical direction and oversight across architecture, system design, development, testing, and production readiness.

• Serve as an escalation point for complex technical issues, data-quality challenges, and delivery risks.

• Design, build, maintain, and optimize scalable data pipelines, integrations, warehouses, and supporting infrastructure.

• Establish and maintain standards for data architecture, modeling, reliability, scalability, performance, maintainability, and data quality.

• Remain hands-on by contributing to development and resolving complex or business-critical technical problems.

• Improve automation, monitoring, tooling, and engineering practices to strengthen the reliability and efficiency of the data environment.

• Define technical direction and priorities for Data Engineering in partnership with business and technical leadership.

• Partner with Finance, Data & Analytics, and other stakeholders to understand business requirements and translate them into effective data solutions.

• Evaluate technologies, processes, and architectural approaches that improve the organization's ability to use, manage, and scale data.

• Communicate technical strategy, infrastructure needs, risks, and recommendations clearly to both technical and non-technical stakeholders.

• Track and improve key outcomes including pipeline reliability, data quality, delivery timeliness, roadmap progress, team development, and stakeholder satisfaction.

• Contribute to special projects and additional responsibilities as business needs evolve.

Requirements

• 7+ years of professional data engineering experience, including at least 2 years leading, supervising, mentoring, or providing technical direction to other engineers.

• Bachelor’s degree in Computer Science, Data Engineering, a related technical discipline, equivalent technical training, or equivalent professional experience.

• Strong hands-on experience designing, building, and maintaining data pipelines, ETL/ELT processes, data warehouses, integrations, and supporting infrastructure.

• Advanced SQL capabilities and strong programming experience with Python, Java, Scala, or a comparable programming language.

• Deep understanding of data architecture, data modeling, scalability, performance optimization, reliability, and data-quality practices.

• Experience with modern cloud data platforms, orchestration frameworks, and data-processing technologies.

• Demonstrated ability to balance hands-on technical contribution with effective team leadership and development.

• Strong business acumen and the ability to translate business requirements into practical, scalable technical solutions.

• Excellent communication and stakeholder-management skills, with the ability to work effectively across technical and non-technical teams.

• Experience with AWS, Azure, or Google Cloud Platform is preferred.

• Familiarity with orchestration and transformation tools such as Airflow, dbt, or comparable technologies is preferred.

• Experience with distributed or streaming data technologies such as Kafka or Spark is a plus.

• Experience with infrastructure-as-code and CI/CD practices for data environments is advantageous.

• Experience establishing, scaling, or maturing a Data Engineering function is preferred.

• Strong ownership mindset, collaborative approach, and commitment to technical quality and continuous improvement.

Benefits

• Remote work opportunity from within the United States.

• Leadership role with significant influence over data engineering strategy and technical direction.

• Opportunity to remain hands-on while leading and developing a Data Engineering team.

• Exposure to cross-functional initiatives spanning Finance, Data & Analytics, and other business functions.

• Opportunity to work with modern cloud data platforms, orchestration technologies, and scalable data infrastructure.

• Collaborative environment focused on ownership, performance, continuous improvement, and professional development.

• Flexible work environment supporting work from home.

• Reasonable workplace accommodations available for qualified individuals with disabilities.