Data Engineer (Mostly Remote)

Responsibilities

• Data Engineering:
• Design, develop, and maintain data pipelines and ETL processes to extract, transform, and load data from various sources into our data warehouse.
• Collaborate with data architects and analysts to ensure data quality, integrity, and consistency across datasets.
• Optimize data structures and storage for efficient data retrieval and analytics performance.
• Implement data governance, security, and compliance measures to protect sensitive information.
• Power BI Dashboard Development:
• Create visually compelling and interactive Power BI dashboards and reports to visualize key performance indicators (KPIs), trends, and insights.
• Customize and configure Power BI visuals, filters, and parameters to meet business requirements and user needs.
• Integrate data from multiple sources into Power BI for comprehensive analytics and reporting capabilities.
• Train and support users in leveraging Power BI for self-service analytics and data exploration.
• Cloud Infrastructure Setup:
• Configure and deploy cloud environments on Azure or AWS, including data storage, compute resources, and services.
• Optimize cloud infrastructure for scalability, reliability, and cost-effectiveness, leveraging best practices and automation tools.
• Monitor cloud performance, security, and resource utilization, implementing continuous improvements and optimizations.
• Collaborate with IT and DevOps teams to integrate data engineering workflows with cloud platforms and services.

Requirements

• Bachelor's degree in Computer Science, Information Technology, or related field (Master's degree preferred).
• 5+ years of experience in data engineering, data modeling, and ETL development.
• Proficiency in Power BI, including dashboard design, DAX expressions, and data modeling techniques.
• Experience with cloud platforms such as Azure (Azure Data Factory, Azure SQL Database) or AWS (AWS Glue, Amazon Redshift).
• Strong SQL skills and knowledge of database systems (SQL Server, MySQL, PostgreSQL, etc.).
• Familiarity with big data technologies (Hadoop, Spark) and machine learning concepts is a plus.
• Excellent problem-solving skills, analytical thinking, and attention to detail.
• Effective communication skills and ability to work collaboratively in a team environment.