Description

You will architect and optimize scalable data systems on GCP to support analytics and real-time decision-making.

This role is on-site.

Responsibilities

• Design and implement scalable data architectures, including data lakes and warehouses on GCP.
• Develop and optimize ETL/ELT pipelines using Python, SQL, and streaming technologies.
• Model and manage knowledge graphs using Neo4j to capture complex data relationships.
• Automate infrastructure and deployments using CI/CD best practices with Terraform and Jenkins.
• Collaborate with data scientists and ML engineers in Agile teams to deliver data-driven solutions.

Required Skills

• 8-15 years of experience in data engineering with expertise in cloud-native architectures.
• Proficiency in Python and SQL for building large-scale ETL/ELT pipelines.
• Hands-on experience with Google Cloud Platform (GCP).
• Experience with distributed systems and real-time data streaming solutions.
• Familiarity with knowledge graphs, specifically Neo4j.
• Understanding of MLOps practices and integrating pipelines with ML workflows.
• Bachelor’s degree in Computer Science or Engineering.

Key Skills

Education

Bachelor’s degree in Computer Science, Engineering