GCP Data Engineer

Job Description :

We are seeking a highly skilled GCP Data Engineer with 5 to 10 years of experience in designing, developing, and managing cloud-based data solutions.

The ideal candidate will have strong expertise in Google Cloud Platform (GCP), Python, BigQuery, and Dataflow or Dataprep.

The role involves building scalable data pipelines, optimizing data processing frameworks, and enabling data-driven decision-making through modern cloud data engineering practices.

Key Responsibilities :

- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows on Google Cloud Platform.

- Build and optimize data processing solutions using GCP-native services and cloud-based architectures.

- Develop and maintain data ingestion, transformation, and integration processes using Python.

- Design, implement, and optimize data models and analytical datasets in BigQuery.

- Develop batch and real-time data processing pipelines using Dataflow or Dataprep.

- Collaborate with business stakeholders, data analysts, and engineering teams to understand and deliver data requirements.

- Ensure data quality, integrity, security, and governance across data platforms.

- Monitor and optimize performance, scalability, and cost efficiency of GCP data solutions.

- Troubleshoot production issues and perform root cause analysis for data pipeline failures.

- Participate in code reviews, testing, deployment, and continuous improvement initiatives.

- Maintain technical documentation and adhere to data engineering best practices.

Required Skills & Experience :

- 5 to 10 years of experience in Data Engineering and Data Platform development.

- Strong hands-on experience with Google Cloud Platform (GCP) data engineering services.

- Proficiency in Python for data processing, automation, and pipeline development.

- Extensive experience with BigQuery, including data modeling, query optimization, and performance tuning.

- Hands-on experience with Dataflow or Dataprep for data transformation and processing.

- Strong understanding of ETL/ELT concepts and modern data engineering practices.

- Experience working with large-scale structured and semi-structured datasets.

- Strong SQL skills and experience designing efficient data solutions.

- Knowledge of data warehousing, data lakes, and cloud-native analytics architectures.

- Experience implementing data quality, validation, and monitoring frameworks.

- Excellent analytical, troubleshooting, and problem-solving skills.

- Strong communication and collaboration abilities.

(ref:hirist.tech)