Senior GCP Data Engineer

GCP Data Engineer

We are seeking an experienced GCP Data Engineer (Senior Level) with 7+ years of expertise in ETL, Data Warehousing, and Data Engineering. The ideal candidate will have hands-on experience with GCP technologies, strong data analysis and design skills, and a deep understanding of modern Data Warehousing and Data Engineering principles.

Qualifications

• Experience: 7+ years in ETL and Data Warehousing.
• Proven experience in developing Data Engineering solutions using:
• Airflow, GCP BigQuery, Cloud Storage, Dataflow, Cloud Functions, Pub/Sub, Cloud Run, etc.
• Hands-on experience with automation in ETL tools and GCP services.
• Successfully executed at least two end-to-end GCP Cloud Data Warehousing projects.
• Experience in Agile/SAFe project delivery methodologies (minimum two projects).
• Proficiency in PySpark and Teradata (mid to advanced level).
• Working knowledge of DevOps tools such as GitHub, Jenkins, and Cloud Native services.
• Experience handling semi-structured data formats (JSON, Parquet, XML).
• Strong ability to write and optimize complex SQL queries for data analysis and extraction.
• In-depth understanding of Data Warehousing, Data Analysis, Data Profiling, Data Quality, and Data Mapping.
• Excellent leadership, communication, and collaboration skills.
  
  

Certifications

• Google Cloud Professional Data Engineer Certification (preferred).
  
  

Roles & Responsibilities

Roles & Responsibilities

• Design, develop, and deploy data pipelines and ETL processes.
• Implement robust data integration solutions to ensure efficient and reliable data flow across multiple systems.
• Collaborate closely with data architects and business analysts to gather requirements and translate them into scalable technical solutions.
• Develop and maintain data transformation and data cleansing processes to ensure high data quality and consistency.
• Monitor, troubleshoot, and optimize data pipelines for performance, scalability, and cost efficiency.
• Lead the automation of data workflows and implement best practices for pipeline management.
• Mentor junior engineers and contribute to defining data engineering standards and frameworks.