Job Description:

• Design, develop, and maintain data transformation processes to cleanse, transform, and aggregate data within the data warehouse.
• Optimize and streamline data workflows to ensure efficient data processing and storage in the data warehouse.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and implement appropriate data transformations.
• Develop and maintain data warehouse schemas, tables, and views to support reporting and analytics needs.
• Implement data governance policies and standards to ensure data quality, security, and compliance.
• Monitor data warehouse performance, troubleshoot issues, and optimize for scalability and efficiency

Requirements:

• Associate's degree or Bachelor’s degree in Computer Science, Informatics Engineering, or a related field with data processing.
• 2+ years of professional experience as a Data Engineer or similar role, with a focus on data warehousing, data pipelining, modeling, and transformation.
• Strong Proficiency in programming languages: Python and SQL
• Experience with application orchestration, Docker and Kubernetes
• Experience with API integration techniques and tools for data extraction, including RESTful APIs, JSON, and OAuth.
• Have a strong understanding and are familiar with data pipeline, data modeling, Kimball data warehouse concept, star schema, and ETL processes.
• Experience with cloud platforms such as AWS, Google Cloud Platform for deploying and managing data pipelines
• Experience with cloud data warehouses such as: Google BigQuery and Snowflake
• Ability to optimize data pipelines and query performance in a large-scale data warehouse.
• Excellent analytical and problem-solving skills, with attention to detail and data accuracy.
• Strong communication skills to work effectively in cross-functional teams and present data solutions to stakeholders.