ResponsibilitiesA Data Architect is an IT expert who enables data-driven decision making by collecting, transforming, and publishing data. At NTT Data, a Data Architect should be able to design, build, operationalize, secure, and monitor data processing systems with a focus on security, compliance, scalability, efficiency, reliability, fidelity, flexibility, and portability. The main mission of a Data Architect is to turn raw data into information, creating insights and business value.Build large-scale batch and real-time data pipelines using data processing frameworks on the GCP cloud platform.Apply an analytical, data-driven approach to understand rapidly changing business needs.Collaborate with the team to evaluate business needs and priorities, liaise with key business partners, and address team requirements related to data systems and management.Participate in project planning by identifying milestones, deliverables, and resource requirements; track activities and task execution.Required SkillsBachelor’s degree in Computer Science, Computer Engineering, or a relevant field.5 to 10 years of experience in a data engineering role.Proficiency as a software engineer using Scala, Java, or Python.Advanced SQL skills, preferably with BigQuery.Good knowledge of Google Managed Services such as Cloud Storage, BigQuery, Dataflow, Dataproc, and Data Fusion.Experience with workflow management systems.Strong understanding of GCP architecture for batch and streaming data processing.Solid knowledge of data technologies and data modeling.Experience in building modern, cloud-native data pipelines and operations following an ELT philosophy.Experience with data migration and data warehousing.Ability to organize, normalize, and store complex data effectively, supporting both ETL processes and end-user needs.Passion for designing ingestion and transformation processes for data from multiple sources to create cohesive data assets.Good understanding of developer tools, CI/CD practices, etc.Excellent communication skills with empathy for end users and internal customers.Nice-to-have :Experience with Big Data ecosystems such as Hadoop, Hive, HDFS, HBase.Experience with Agile methodologies and DevOps principles.J-18808-Ljbffr
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