GCP Data Engineer​/Data Architect

Responsibilities
A 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 platform
Use 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 execution
Required Skills
Bachelor’s degree in Computer Science, Computer Engineering or relevant field
At least 5 - 10years’ experience in a data engineering role
Expertise as a software engineering using Scala / Java / Python
Experience in Advanced SQL skillset - preference on using Big Query
Good knowledge on Google Managed Services as Cloud Storage, Big Query, Dataflow, Dataproc, and Data Fusion
Experience using workflow management
Good understand of GCP Architecture batch and streaming
Strong knowledge of data technologies and data modeling
Expertise on building modern, cloud-native data pipelines and operations, with an ELT philosophy

Experience with Data Migration / Data Warehouse
Intuitive thinking of how to organize, normalize, and store complex data, enabling both ETL and end users
Passion for mapping and designing ingestion and transformation of data from multiple sources, creating a cohesive data asset
Good understanding of developer tools, CICD etc
Excellent communication, empathetic with end users and internal customers.
Nice-to-have :
Experience using Big Data echo system Hadoop, Hive, HDFS, Hbase

Experience with Agile methodologies and Dev Ops principles

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