Description

You will design and deploy data-centric architectures on Google Cloud Platform to support Materials Management across product development, manufacturing, finance, and supply chain domains.

Responsibilities

• Design and implement data-centric solutions using BigQuery, Cloud Storage, Cloud SQL, Dataflow, Dataproc, and Vertex AI.
• Build ETL pipelines using Java and Python to ingest data from modern and legacy heterogeneous sources.
• Create and maintain data models to ensure efficient storage and retrieval of large datasets.
• Optimize data workflows for performance, reliability, and cost-effectiveness on GCP infrastructure.
• Implement CI/CD practices and version control for data engineering workflows.
• Address code quality and security using SonarQube, Checkmarx, Fossa, and Cycode.
• Manage SQL and NoSQL databases including Bigtable, Firestore, and Cloud SQL.
• Monitor system performance using GCP logging tools and participate in on-call rotations.

Required Skills

• 5+ years of experience in data architecture or data engineering.
• Extensive experience with Google Cloud Platform (GCP) services.
• Proficiency in Python and Java for data processing.
• Deep knowledge of BigQuery and Google Cloud Storage.
• Hands-on experience with Cloud SQL and SQL database management.
• Experience building ETL/ELT pipelines and data workflows.
• Practical application of CI/CD practices.
• Experience with code quality tools including SonarQube, Checkmarx, and Fossa.
• Ability to manage both SQL and NoSQL environments.

Key Skills

Education

Any Gradute