Verified Job
Engineering - Architecture
GCP Data Engineer_Pyspark/Scala
Engineering - Architecture
#778685
Remote / WFH
Zorba AI
Job Description
We are looking for a highly skilled GCP Data Engineer with 5+ years of experience in designing and building scalable data solutions on Google Cloud Platform. The ideal candidate will have strong expertise in BigQuery, Python, and modern data engineering practices, with a focus on performance, reliability, and cost optimization.
Key Responsibilities
• Design, develop, and maintain scalable and robust data pipelines on GCP
• Build and optimize data warehouses using BigQuery (partitioning, clustering, query tuning)
• Develop ETL/ELT pipelines using Python and GCP-native tools
• Integrate data from multiple sources including APIs, databases, and streaming platforms
• Ensure high performance and cost efficiency of data processing systems
• Collaborate with data analysts, data scientists, and business stakeholders
• Implement data quality checks, governance, and security standards
• Monitor, debug, and optimize data workflows and pipelines
• Support batch and real-time data processing requirements
Required Skills
• 5+ years of hands-on experience in Data Engineering
• Strong experience with Google Cloud Platform (GCP)
• Expertise in BigQuery (data modeling, performance tuning)
• Strong programming skills in Python (Pandas; PySpark is a plus)
• Experience with Cloud Composer / Apache Airflow
• Knowledge of Cloud Storage, Pub/Sub, Dataflow
• Advanced SQL and strong data warehousing concepts
• Experience building scalable ETL/ELT pipelines
Preferred Skills
• Experience with Apache Spark / Databricks
• Familiarity with CI/CD pipelines and DevOps practices
• Knowledge of data visualization tools like Tableau / Looker
• Experience with streaming data processing
• Exposure to data lake / lakehouse architectures
Educational Qualification
• Bachelors or Master’s degree in Computer Science, IT, or related field
Good to Have
• GCP Certification (e.g., Professional Data Engineer)
• Experience working in Agile/Scrum environments
Skills: spark,python,scala,gcp
Key Responsibilities
• Design, develop, and maintain scalable and robust data pipelines on GCP
• Build and optimize data warehouses using BigQuery (partitioning, clustering, query tuning)
• Develop ETL/ELT pipelines using Python and GCP-native tools
• Integrate data from multiple sources including APIs, databases, and streaming platforms
• Ensure high performance and cost efficiency of data processing systems
• Collaborate with data analysts, data scientists, and business stakeholders
• Implement data quality checks, governance, and security standards
• Monitor, debug, and optimize data workflows and pipelines
• Support batch and real-time data processing requirements
Required Skills
• 5+ years of hands-on experience in Data Engineering
• Strong experience with Google Cloud Platform (GCP)
• Expertise in BigQuery (data modeling, performance tuning)
• Strong programming skills in Python (Pandas; PySpark is a plus)
• Experience with Cloud Composer / Apache Airflow
• Knowledge of Cloud Storage, Pub/Sub, Dataflow
• Advanced SQL and strong data warehousing concepts
• Experience building scalable ETL/ELT pipelines
Preferred Skills
• Experience with Apache Spark / Databricks
• Familiarity with CI/CD pipelines and DevOps practices
• Knowledge of data visualization tools like Tableau / Looker
• Experience with streaming data processing
• Exposure to data lake / lakehouse architectures
Educational Qualification
• Bachelors or Master’s degree in Computer Science, IT, or related field
Good to Have
• GCP Certification (e.g., Professional Data Engineer)
• Experience working in Agile/Scrum environments
Skills: spark,python,scala,gcp
