Gcp Data Engineer

Job Summary

We are looking for an experienced GCP Data Engineer with 46 years of hands-on experience in designing, developing, and maintaining cloud-based data pipelines and data solutions. The ideal candidate should have strong expertise in GCP, BigQuery, Cloud Storage, Python, Apache Airflow, Cloud Functions/Cloud Run, MS SQL Server, and GitHub.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and data solutions on Google Cloud Platform (GCP).
• Develop and manage data workflows using Apache Airflow.
• Build and optimize data solutions using Google BigQuery and Google Cloud Storage (GCS).
• Develop Python-based applications, scripts, and data-processing solutions.
• Work with Cloud Functions and Cloud Run for serverless processing and application deployment.
• Develop complex SQL queries, stored procedures, and data transformations using MS SQL Server.
• Implement event-driven solutions using GCP Triggers and Pub/Sub.
• Perform data extraction, transformation, validation, and loading across multiple data sources.
• Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and data quality.
• Follow best practices for cloud security, scalability, maintainability, and cost optimization.
• Use GitHub for source-code management, version control, and collaborative development.
• Participate in code reviews, testing, deployment, and technical documentation.
• Collaborate with data analysts, architects, developers, and business stakeholders to understand requirements and deliver effective solutions.

Required Skills

• 4–6 years of experience in Data Engineering or a related role.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Hands-on experience with Google BigQuery.
• Good knowledge of Google Cloud Storage (GCS).
• Strong programming skills in Python.
• Hands-on experience with Apache Airflow.
• Experience with Cloud Functions and/or Cloud Run.
• Strong SQL skills with experience in MS SQL Server.
• Experience with Git/GitHub and version-control practices.
• Good understanding of ETL/ELT concepts, data pipelines, and data warehousing.
• Strong problem-solving, debugging, and analytical skills.

Nice to Have

• Hands-on experience with Node.js.
• Experience using AI-assisted development tools such as Cursor, Claude, MCP, or similar tools.
• Experience with GCS and cloud-based data storage solutions.
• Experience working with GCP Triggers and event-driven architectures.
• Knowledge of Google Cloud Pub/Sub for asynchronous messaging and event-driven processing.
• Exposure to integrating AI tools into software development, automation, or data engineering workflows.
• Familiarity with CI/CD practices for cloud-based applications and data pipelines.
• Understanding of GCP IAM, monitoring, logging, and security practices.
• Experience optimizing BigQuery queries and data-processing costs.