Leading, designing, developing, and maintaining scalable and robust data pipelines and infrastructure within Roche’s DataOne ecosystem. This role involves independently building ETL/ELT processes, optimizing data storage solutions such as data warehouses and data lakes, ensuring data quality and reliability, and monitoring data systems. You will collaborate closely with data scientists and analysts to meet their specific data requirements, implementing decentralized Data Products following Data Mesh principles, utilizing strong programming skills in Python, expert SQL knowledge, and proficiency in big data technologies like Snowflake.

Siga leyendo para descubrir lo que necesitará para tener éxito en este puesto, incluyendo habilidades, cualificaciones y experiencia.
The Position
The Security Insights and Automation Data Engineer
Job Responsibilities

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- Data Architecture & Pipeline Engineering: Leads the design, build, and maintenance of scalable end-to-end data pipelines using Talend, dbt, and Python. Ensure all architectures are scalable, secure, and aligned with the Data Mesh standards.

- Security Intelligence Support: Transform raw security telemetry and vulnerability data into high-quality feature sets for predictive modeling, anomaly detection, and automated risk scoring.

- Stakeholder Management: Engages directly with broader business units and data scientists to thoroughly understand and meet their data needs. Communicates effectively with both technical and non-technical stakeholders.

- Visualization & Insights: Support the mastery of Tableau and ThoughtSpot by ensuring underlying data structures and schemas are optimized for intuitive executive narratives and self-service analytical apps.

- System Optimization:



Solve complex data ingestion problems and perform expert-level Snowflake table optimizations and schema designs. Leads high-impact, large-scale data engineering initiatives by implementing robust strategies and integrating complex, diverse infrastructures to ensure seamless organizational data flow.

Qualifications
Education / Experience

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- Demonstrated experience handling big-sized data engineering projects and managing complex, large-scale data systems.

- Proven track record of independently building ETL/ELT processes and optimizing data storage solutions such as data warehouses and data lakes.

- Experience ensuring data quality, reliability, and monitoring data systems.

Technical Skills

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- Expert SQL & Snowflake: Advanced proficiency in designing Snowflake data structures, schemas, and performance optimizations.

- Advanced Programming: Expert-level Python or Scala for data engineering and Gitlab for version control and orchestration.

- Modern Data Stack: Hands‑on experience with dbt for transformation and Talend for integration.

- Data Mesh & AI/ML: Solid understanding of decentralized Data Mesh principles and preparing data for AI/ML initiatives (e.g., feature engineering).

- BI Tooling: Technical capability to support advanced visualizations in Tableau and ThoughtSpot.

- API Integration: Expertise in consuming and exposing APIs to integrate security insights across the enterprise ecosystem.

Additional Qualifications

Exceptional communication and collaboration skills, with the proven ability to engage effectively with both technical audiences (like data scientists) and non‑technical business stakeholders. xqbhyrx

Roche is an Equal Opportunity Employer.

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📌 Data Engineer - Security Insights and Automation (Madrid)
🏢 Roche
📍 Madrid