06 lug
Novara
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 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.
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