Data Engineering Manager
Lead and mentor a team of data infrastructure engineers. Define and execute the technical roadmap for data platforms, ensuring scalability, reliability, and high availability. Oversee architecture and pipeline development. Partner with cross-functional teams to support analytics and machine learning initiatives. Drive operational excellence through monitoring, automation, and incident management.
Responsibilities
- Lead, mentor, and manage a team of data infrastructure engineers.
- Define and execute the technical roadmap for the data infrastructure platform.
- Oversee architecture, scalability, and reliability of data systems and pipelines.
- Establish data quality standards, monitoring, and validation processes.
- Partner with engineering and product teams to enable scalable data foundations for analytics and AI.
- Drive operational excellence through monitoring, observability, automation, and incident management.
- Manage end-to-end technical projects from design to production.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or related field.
- 7+ years of experience in software, data, or infrastructure engineering.
- 2+ years of experience managing or leading engineering teams.
- Experience with distributed systems and large-scale data platforms.
- Hands-on experience with Kafka, Spark, Flink, Airflow, DBT, Snowflake, or similar technologies.
- Proficiency in Java, Scala, or Python.
- Experience with cloud platforms (AWS, GCP, or Azure).
- Strong understanding of system reliability, performance optimization, and operational best practices.
- Excellent communication and stakeholder management skills.
Nice to have
- Experience with real-time streaming and event-driven architectures.
- Experience managing high-scale production environments.
- Familiarity with Kubernetes and containerized infrastructure.
- Experience leading platform modernization or migration initiatives.
- Knowledge of CI/CD pipelines and infrastructure automation tools.