AD - Data Engineer - 0007
Description For AD - Data Engineer - 0007
We are seeking a skilled Data Engineer to join our dynamic team at Thaloz. The role focuses on designing, building, and maintaining scalable data pipelines while ensuring data integrity and availability for analysis. As a Data Engineer, you'll work with Python, SQL, and PySpark to process large datasets in a distributed computing environment. You'll collaborate closely with data scientists and analysts to support data-driven decision-making across the organization. The position requires expertise in data warehousing, ETL processes, and cloud-based technologies, particularly Databricks. Working in an Agile environment, you'll participate in sprint planning and use Jira for project management. The ideal candidate brings 3+ years of experience, strong problem-solving abilities, and excellent communication skills. This remote position offers an opportunity to work with cutting-edge data technologies while contributing to the company's data infrastructure and analytics capabilities.
Responsibilities For AD - Data Engineer - 0007
- Design, develop, and maintain robust data pipelines to process large volumes of data from various sources
- Collaborate with data scientists and analysts to understand data requirements and deliver high-quality datasets
- Optimize data storage and retrieval processes to improve performance and efficiency
- Implement data quality checks and monitoring to ensure the accuracy and reliability of data
- Work with cloud-based technologies, particularly Databricks, to manage and analyze data
- Participate in Agile development processes, including sprint planning and retrospectives using Jira
- Document data processes, architectures, and workflows for future reference and compliance
- Stay updated with industry trends and best practices in data engineering and analytics
Requirements For AD - Data Engineer - 0007
- Proficient in Python as a core programming language for data manipulation and analysis
- Strong knowledge of SQL for querying databases and performing data transformations
- Experience with PySpark for processing large datasets in a distributed computing environment
- Familiarity with Databricks is a plus, enabling efficient data processing and collaboration
- Understanding of data warehousing concepts and ETL processes
- Experience working in Agile environments, particularly with Scrum methodologies
- Proficient in using Jira for project management and tracking progress
- Minimum of 3 years of experience in data engineering or related fields
- Proven track record of building and maintaining data pipelines in production environments
- Excellent communication skills to effectively collaborate with cross-functional teams
- Strong problem-solving abilities and attention to detail
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