Data Engineering Manager
New
Based in United StatesFull-TimeManager
SalaryCompetitive annual salary of approximately $220,000.
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Job Details
- Experience
- 7+ years of experience managing engineering teams
- Required Skills
- DockerAgileCloud ComputingKubernetesPeople ManagementAirflowData engineeringDistributed Systems
Requirements
- 7+ years of experience managing engineering teams, with a proven ability to build and lead high-performing teams.
- Strong technical expertise in distributed data systems and modern data engineering practices.
- Previous hands-on engineering experience with technologies such as Airflow, Elastic Stack, Docker, Kubernetes, and cloud platforms.
- Ability to contribute to technical discussions, troubleshooting, and hands-on development when needed.
- Experience managing Agile development processes and collaborating effectively with cross-functional product teams.
- Strong leadership, communication, and presentation skills with the ability to influence technical decisions.
- Detail-oriented mindset with strong ownership, initiative, and commitment to quality.
- Experience working with cybersecurity data, threat detection, threat intelligence, or industrial security environments is a plus.
Responsibilities
- Lead, mentor, and develop a team of data engineers by supporting technical growth, career progression, and team performance.
- Define and execute the vision for scalable data processing systems and data engineering strategies aligned with business objectives.
- Partner with product and engineering teams to design data architectures and develop effective technical solutions.
- Build strong relationships across engineering leadership teams to encourage collaboration, knowledge sharing, and technical alignment.
- Establish engineering best practices, coding standards, and performance optimization strategies across data initiatives.
- Provide technical guidance throughout software design, development, testing, deployment, and production support processes.
- Balance delivery priorities, technical debt management, and long-term innovation to ensure sustainable platform growth.
- Support production systems and ensure reliable operation of deployed data solutions.
- Stay informed on emerging data technologies, frameworks, and industry best practices to continuously improve engineering capabilities.
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