Data Architect

About the role

Data Architect (Ref.No. R1013111) at our location in Singapore Hitachi Rail is seeking an enthusiastic and self-motivated Data Architect with strong experience in designing and delivering scalable data solutions. The ideal candidate brings deep expertise in data architecture, data platforms, and analytics ecosystems, combined with solid leadership capabilities. This role is responsible for defining robust, secure, and high-performance data architectures to support asset management and predictive maintenance solutions. The Data Architect will ensure data is structured, governed, and accessible to enable advanced analytics and data-driven decision-making. The candidate will collaborate closely with cross-functional teams to translate business requirements into effective data solutions and drive the advancement of Hitachi Rail's HMAX initiatives. You will enjoy having these responsibilities: Define and design end-to-end data architecture across data ingestion, storage, processing, and consumption layers. Translate business requirements into scalable, secure, and high-performance data solutions. Develop and maintain data models (conceptual, logical, physical) to support analytics and operational use cases. Design and enable data platforms (data lakes, warehouses, lakehouse architectures) for structured and unstructured data. Establish data integration frameworks, including ETL/ELT pipelines, APIs, and streaming solutions. Ensure data governance, quality, lineage, and compliance across the data lifecycle. Embed data security principles (access control, encryption, data protection) into architecture design. Support predictive analytics and data-driven use cases through well-structured and accessible data environments. Provide technical leadership across data initiatives, ensuring best practices and standards are applied. Collaborate with stakeholders and act as a trusted advisor on data strategy and architecture. You have: Bachelor or Master Degree in Computer Science/Computer Engineering or related field. Strong experience in data architecture and data platform design. Proven expertise in cloud data platforms (e.g., AWS, Azure, GCP), including modern data architectures. Hands-on knowledge of data processing frameworks (e.g., Spark) and large-scale data handling. Experience with data lakes, data warehouses, and lakehouse architectures. Solid understanding of data integration patterns (ETL/ELT, APIs, streaming, messaging). Familiarity with data governance frameworks, metadata management, and data quality practices. Knowledge of data security and privacy principles, including IAM, encryption, and compliance. Experience with DevOps/DataOps practices, including CI/CD and automation for data pipelines. Understanding of distributed systems and scalable data architectures. Experience with monitoring, logging, and observability for data platforms. Exposure to predictive analytics or data-driven solutions is an advantage. Strong analytical, problem-solving, and communication skills with cross-functional collaboration experience Proficiency in Italian would be an advantage for communication with Italian-speaking stakeholders.

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