Google Cloud Platform Data Engineer

Google Cloud Platform Data Engineer

Detailed JD:

Designs, builds, and maintains scalable data pipelines and architectures on Google Cloud, transforming raw data into accessible insights using tools like BigQuery, Dataflow, and Cloud Storage, ensuring quality, security, and performance, while collaborating with analysts and scientists to meet business needs.

Key responsibilities include ETL/ELT, data warehousing, monitoring, and optimizing cloud data solutions, requiring skills in SQL, Python, and Google Cloud Platform services, along with strong analytical and communication abilities. 

Responsibilities

• Pipeline Development: Design, build, and maintain robust, scalable data pipelines (batch/streaming) using Google Cloud Platform services.
• Architecture: Develop and manage data warehousing and data lake solutions (e.g., BigQuery, Cloud Storage).
• Data Quality & Governance: Ensure data integrity, consistency, security, and compliance.
• Collaboration: Work with data scientists, analysts, and business stakeholders to define requirements and deliver solutions.
• Optimization: Monitor and optimize data infrastructure for performance, cost, and reliability.
• Automation: Implement CI/CD, Infrastructure as Code (IaC), and automation for data workflows. 

Core Skills & Qualifications

• At least 3+ years of experience with Google Cloud Platform data services (BigQuery, Dataflow, Dataproc, Cloud Storage, etc.).
• Must have delivered al least 2 to 3 end to end projects as a data engineer using Google Cloud Platform Services
• Strong understanding of database design, data modeling (relational, dimensional, NoSQL).
• Expertise in data integration, ETL/ELT, and data pipeline development.
• Knowledge of cloud security best practices, identity management, and networking.
• Familiarity with DevOps, CI/CD, and containerization (Docker, Kubernetes).
• Excellent communication, problem-solving, and leadership skills.