ResponsibilitiesA Data Architect is an IT expert that enables data-driven decision making by collecting, transforming, and publishing data. In NTT Data, a Data Architect should be able to design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance, scalability and efficiency, reliability and fidelity, flexibility and portability. The main mission of a Data Architect is to turn raw data into information creating insight and business value.Build large-scale batch and real-time data pipelines with data processing frameworks in GCP cloud platformUse an analytical, data-driven approach to drive a deep understanding of fast changing business.Work with the team to evaluate business needs and priorities, liaise with key business partners and address team needs related to data systems and management.Participate in project planning; identifying milestones, deliverables and resource requirements; tracks activities and task executionRequired SkillsBachelor's degree in Computer Science, Computer Engineering or relevant fieldAt least 5 - 10years' experience in a data engineering roleExpertise as a software engineering using Scala / Java / PythonExperience in Advanced SQL skillset - preference on using BigQueryGood knowledge on Google Managed Services as Cloud Storage, BigQuery, Dataflow, Dataproc, and Data FusionExperience using workflow managementGood understand of GCP Architecture batch and streamingStrong knowledge of data technologies and data modelingExpertise on building modern, cloud-native data pipelines and operations, with an ELT philosophyExperience with Data Migration / Data WarehouseIntuitive thinking of how to organize, normalize, and store complex data, enabling both ETL and end usersPassion for mapping and designing ingestion and transformation of data from multiple sources, creating a cohesive data assetGood understanding of developer tools, CICD etcExcellent communication, empathetic with end users and internal customers.Nice-to-have :Experience using Big Data echo system Hadoop, Hive, HDFS, HbaseExperience with Agile methodologies and DevOps principles
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