About the role
Must Have-
- Expertise in Google Data Engineering services Big Query, Dataproc, etc
- Strong experience in programming languages such as Python, PySpark data manipulation and engineering tasks.
- Expertise in SQL and NoSQL databases
- In-depth knowledge of data warehousing solutions
- Deep understanding on data warehousing concepts
- Proficiency in designing, developing, and maintaining ETL (Extract, Transform, Load) processes using tools like Apache Airflow, Talent, or Informatica.
- Design, develop, and maintain scalable data pipelines for extracting, transforming, and loading data from various sources to ensure seamless data flow and accessibility.
- Collaborate with cross-functional teams to integrate data from multiple disparate sources, ensuring consistency, accuracy, and reliability of data.
- Optimize data processing workflows and storage solutions for performance, scalability, and cost-efficiency
- Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of data throughout the data lifecycle.
- Monitor the performance of data pipelines and infrastructure, identifying and resolving issues to maintain system stability and reliability.