
Senior Cloud Data Engineering Professional
4 days ago
We are seeking an experienced and skilled Data Engineer to join our team.
As a pivotal member of our data engineering team, you will play a crucial role in designing, implementing, and optimizing data pipelines, ensuring seamless integration with cloud platforms.
The ideal candidate will possess a strong command of Python, data engineering principles, and a proven track record of successful implementation of scalable solutions in cloud environments.
- Data Pipeline Development:
- Design, develop, and maintain scalable and efficient data pipelines using Python and cloud-based technologies.
- Implement Extract, Transform, Load (ETL) processes to seamlessly move data from diverse sources into our cloud-based data warehouse.
- Cloud Integration:
- Utilize cloud platforms (e.g., Google Cloud, AWS, Azure) to deploy, manage, and optimize data engineering solutions.
- Leverage cloud-native services for storage, processing, and analysis of large datasets.
- Collaboration and Communication:
- Work closely with data scientists, analysts, and other teams to understand data requirements and provide technical support.
- Collaborate with other engineering teams to seamlessly integrate data engineering solutions into larger cloud-based systems.
Proficiency in Python for data engineering tasks, scripting, and automation.
Extensive experience with data engineering frameworks like distributed data processing.
Understanding and hands-on experience with workflow management tools like Apache Airflow.
In-depth knowledge and hands-on experience with at least one major cloud platform: AWS, Azure, or Google Cloud.
Familiarity with cloud-native services for data processing, storage, and analytics.
Proven expertise in designing and implementing Extract, Transform, Load (ETL) processes.
SQL and Databases: Proficient in SQL with experience in working with relational databases (e.g., PostgreSQL, MySQL) and cloud-based database services.
Version Control: Familiarity with version control systems, such as Git, for tracking changes in code and configurations.
Containerization and Orchestration: Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes).
Monitoring and Troubleshooting: Ability to implement monitoring solutions and troubleshoot issues in data pipelines.
Agile Methodologies: Familiarity with agile development methodologies and practices.
Soft Skills:
- Strong problem-solving and critical-thinking abilities.
- Excellent communication skills, both written and verbal.
- Ability to work collaboratively in a cross-functional team environment.
- Attention to detail and commitment to delivering high-quality solutions.
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