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Data Infrastructure Engineering Manager
HíbridoTiempo completoEngineering ManagementBiotechnology
Lead a multidisciplinary data infrastructure team responsible for building, productionizing, and improving big data and analytics systems. Own delivery, technical quality, agile practices, and team development in a hybrid Israel-based role.
Responsabilidades
- Lead, manage, and develop a data infrastructure team of approximately five to seven people.
- Own team planning, prioritization, execution, delivery, and continuous improvement.
- Lead Scrum-based agile practices and improve delivery predictability.
- Guide the design, productionization, and ongoing improvement of big data and analytics infrastructure.
- Support architectural and technical decisions across cloud infrastructure, data pipelines, orchestration, and production systems.
- Promote AI-assisted development workflows, automation, and AI-first engineering practices.
- Improve team processes, technical quality, collaboration, and engineering standards.
- Partner with stakeholders across technical, scientific, and business functions.
- Create an environment that supports team growth, contribution, and continuous improvement.
Requisitos
- At least 5 years of experience leading data engineering, data infrastructure, or related engineering teams of five or more people.
- Strong technical background in data infrastructure, cloud computing, and production systems.
- Hands-on experience with data warehousing tools such as Snowflake or BigQuery.
- Hands-on experience with orchestration tools such as Dagster or Apache Airflow.
- Experience developing in Python and productionizing big data, analytics, or data platform infrastructure.
- Experience leading agile teams using Scrum methodologies.
- Ability to lead multidisciplinary teams and collaborate across technical, scientific, and business functions.
- Track record of improving processes, automation, technical quality, or delivery practices.
- Strategic judgment connecting technical decisions with team and business goals.
- Strong written and spoken English communication skills for working with an international, multilingual team.
Se valora
- Experience in scientific, biotechnology, immunology, life sciences, or biology-related environments.
- Familiarity with agentic AI concepts, tools, or development patterns.
- Experience supporting AI-first development processes for software or data engineering teams.
- Experience with modern automation across engineering workflows, infrastructure, and delivery pipelines.