ResponsibilitiesA Data Architect is an IT expert responsible for enabling data-driven decision making by collecting, transforming, and publishing data. At NTT Data, a Data Architect should be capable of designing, building, operationalizing, securing, and monitoring data processing systems with a focus on security, compliance, scalability, efficiency, reliability, fidelity, flexibility, and portability. The primary goal of a Data Architect is to convert raw data into information, generating insights and business value.Build large-scale batch and real-time data pipelines using data processing frameworks on the GCP cloud platform.Apply analytical, data-driven approaches to gain a deep understanding of rapidly changing business needs.Collaborate with teams 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 needs; track activities and task execution.Required SkillsBachelor’s degree in Computer Science, Computer Engineering, or a related field.5-10 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 tools.Solid understanding of GCP architecture for batch and streaming data processing.Strong knowledge of data technologies and data modeling.Expertise in building modern, cloud-native data pipelines and operations following an ELT approach.Experience with data migration and data warehousing.Ability to organize, normalize, and store complex data to support 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 pipelines, etc.Excellent communication skills, with empathy towards 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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