GCP Data Engineer/Data Architect

1 mese fa

Italia NTT DATA Corporation A tempo pieno

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 - 10 years’ experience in a data engineering role.
  • Expertise as a software engineering using Scala/Java/Python.
  • Experience in Advanced SQL skillset - preference on using BigQuery.
  • Good knowledge on Google Managed Services as Cloud Storage, BigQuery, Dataflow, Dataproc, and Data Fusion.
  • Experience using workflow management.
  • Good understanding 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 ecosystem Hadoop, Hive, HDFS, Hbase.
  • Experience with Agile methodologies and DevOps principles.
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