Data Architect

Your responsibilities will include:

• Crafting and structuring comprehensive data architecture that spans data ingestion, storage, processing, and consumption layers.
• Transforming business requirements into robust, scalable, secure, and high-performance data solutions.
• Creating and sustaining data models (conceptual, logical, physical) to facilitate analytics and operational applications.
• Designing and implementing data platforms (data lakes, warehouses, lakehouse architectures) for both structured and unstructured data.
• Developing data integration frameworks, including ETL/ELT pipelines, APIs, and streaming solutions.
• Ensuring adherence to data governance, quality, lineage, and compliance throughout the data lifecycle.
• Integrating data security principles (access control, encryption, data protection) into architecture design.
• Supporting predictive analytics and data-driven initiatives through accessible and well-organized data environments.
• Providing technical leadership across various data initiatives, ensuring the application of best practices and standards.
• Engaging with stakeholders and serving as a trusted advisor on data strategy and architecture.

You will possess:

• A Bachelor’s or Master’s Degree in Computer Science, Computer Engineering, or a related discipline.
• Extensive experience in data architecture and the design of data platforms.
• Demonstrated proficiency in cloud data platforms (e.g., AWS, Azure, GCP), including contemporary data architectures.
• Practical expertise in data processing frameworks (e.g., Spark) and managing large-scale data.
• Experience with data lakes, data warehouses, and lakehouse architectures.
• Strong grasp of data integration patterns (ETL/ELT, APIs, streaming, messaging).
• Familiarity with data governance frameworks, metadata management, and data quality methodologies.
• Understanding of data security and privacy standards, including IAM, encryption, and compliance.
• Experience with DevOps/DataOps practices, including CI/CD and automation for data pipelines.
• A comprehension of distributed systems and scalable data architectures.
• Experience with monitoring, logging, and observability within data platforms.
• Exposure to predictive analytics or data-driven solutions is a plus.
• Strong analytical, problem-solving, and communication abilities, with experience in cross-functional collaboration.
• Proficiency in Italian is advantageous for effective communication with Italian-speaking stakeholders.