Designs, builds, and maintains scalable data pipelines using Python and GCP. Develops complex SQL queries, implements ETL/ELT workflows, supports data warehousing, monitors pipeline performance, troubleshoots issues, and ensures data integrity, security, scalability, and operational continuity through documentation and cross-functional collaboration.
Job Summary
We are seeking a skilled Data Engineer specializing in Python and Google Cloud Platform (GCP) to join our IT Services division. In this pivotal role, you will design, build, and maintain scalable data pipelines that drive business intelligence and operational efficiency. The position demands a deep understanding of cloud-native data architectures, ensuring seamless data integration and high-performance processing within the GCP ecosystem. This opportunity is ideal for a professional with substantial hands-on experience who is eager to leverage advanced analytics to solve complex data challenges.
Key Responsibilities
- Architect and implement robust data ingestion, transformation, and loading workflows using Python and GCP services.
- Develop and optimize SQL queries to extract, manipulate, and analyze large datasets efficiently.
- Collaborate with cross-functional teams to define data requirements and deliver high-quality data solutions.
- Monitor data pipeline performance, troubleshoot issues, and ensure data integrity and security across the platform.
- Maintain and enhance existing data infrastructure to support growing business needs and scalability.
- Document technical designs, processes, and best practices to ensure knowledge sharing and operational continuity.
Requirements
Requirements:
- Experience: 5.5 to 8 years of professional experience in data engineering roles.
- Technical Proficiency: Advanced expertise in Python programming for data manipulation and automation.
- Database Skills: Strong command of SQL for complex querying and data modeling.
- Cloud Platform: Proven hands-on experience with Google Cloud Platform (GCP) data services and tools.
- Domain Knowledge: Solid background in data engineering principles, including ETL/ELT processes and data warehousing.
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