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.

Requirements

Required Skills

• Bachelor’s degree in Computer Science, Computer Engineering or relevant field.
• At least 5 - 10 years’ experience in a data engineering role.
• Expertise as a software engineer using Scala/Java/Python.
• Experience in Advanced SQL skillset - preference on using BigQuery.
• Good knowledge of Google Managed Services such as Cloud Storage, BigQuery, Dataflow, Dataproc, and Data Fusion.
• Experience using workflow management.
• Good understanding of GCP Architecture for batch and streaming.
• Strong knowledge of data technologies and data modeling.
• Expertise in 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 skills, empathetic with end users and internal customers.

Nice-to-have:

• Experience using Big Data ecosystem Hadoop, Hive, HDFS, Hbase.
• Experience with Agile methodologies and DevOps principles.