Data Engineering Lead

hace 2 días

Madrid, Madrid, España Chubb A tiempo completo

Are you ready to lead the design and development of world-class data solutions in a global insurance environment? Chubb European Group is seeking a Data Engineering Lead to architect, build, and optimize our data assets on Azure, Databricks, and Snowflake. This is a strategic, hands-on leadership role for someone passionate about data engineering, agile principles, and driving innovation through technology

Key Responsibilities:

  • Design and architect complex, scalable, and high-performance data-heavy applications on Databricks and Snowflake, applying deep expertise in database architecture, data warehouse design, and cloud computing (Azure VM, Cloud Services).

  • Define and enforce best practices and coding standards for engineering squads, championing Agile principles and values (Scrum, Kanban) to foster team effectiveness and continuous improvement.

  • Lead technical discussions and decision-making, guiding teams through the full development lifecycle—from discovery to go-live—while ensuring projects are delivered on time and meet rigorous quality standards.

  • Act as the principal technical advisor for Data Engineering, collaborating with architects, developers, and product managers to deliver cohesive, impactful data products.

  • Oversee end-to-end development, including requirement analysis, deployment, and performance tuning (DB/SQL optimization), ensuring robust, error-free applications.

  • Mentor and guide junior and senior Data Engineers, sharing knowledge through workshops, training sessions, and comprehensive documentation of architecture, design patterns, and development processes.

  • Promote a collaborative and innovative team environment, facilitating effective communication between technical and non-technical stakeholders.

  • Conduct code reviews and advocate for automated testing practices, leveraging automation frameworks (Selenium, Appium, Robot Framework) and tools (Puppet, Ansible, Terraform) to ensure reliability and maintainability.

  • Identify performance bottlenecks and implement optimizations, supporting database maintenance, backups, and disaster recovery.

  • Stay current with industry trends, exploring and prototyping new technologies and methodologies for continuous improvement.

  • Lead initiatives in data cleansing, curation, harmonization, and feature engineering, ensuring data quality and integration align with organizational goals.

  • Design and implement secure, compliant data strategies, applying knowledge of data privacy, security, and regulations (GDPR, HIPAA, CCPA) to protect sensitive information.

  • Develop and manage data pipelines/ETL processes, master data management, and open data standards for system interoperability.

  • Apply advanced analytical skills to interpret complex data sets, build meaningful models, and drive data-driven decision-making.

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