Responsibilities
- Develop and manage ETL processes to support data integration and transformation.
- Optimize data storage solutions for enhanced performance and scalability.
- Ensure high data quality and integrity across all data projects.
- Collaborate with cross-functional teams to define data requirements and support analytics initiatives.
- Implement cloud services to streamline data management and accessibility.
- Enhance existing data pipelines to improve efficiency and reliability.
- Document processes and maintain comprehensive data architecture records
- Implement data visualization solutions as required by stakeholders.
- Perform data modeling and schema design to support reporting needs.
- Monitor data quality and ensure data integrity across platforms.
- Optimize SQL queries for performance improvements.
- Develop ETL processes to integrate data from various sources into BigQuery.
- Maintain and troubleshoot existing data infrastructure.
- Evaluate new GCP services and tools for data engineering solutions.
Required Skills
- Proficient in MySQL and SQL for database management.
- Strong experience in Python programming & PySpark for data processing.
- Data Engineering experience using GCP (BigQuery, DataProc, Cloud Composer)
- Expertise in developing and optimizing ETL processes.
- Comprehensive understanding of data warehousing concepts.
- Strong written and verbal communication skills, with attention to detail.
- Experience with data pipeline construction and management.
- Familiarity with cloud services for data storage and processing.
- Experience with Data Visualization tools like Tableau, Power Bi, Looker.
Preferred - GCP Certification: GCP Data Engineer/Cloud DB Engineer
