Data Engineer Charlotte, NC

Responsibilities

• Develop and maintain robust data pipelines and ETL processes to facilitate seamless data integration across various platforms.
• Utilize Microsoft SQL Server and SSIS stack for data management and transformation tasks.
• Design and manage cloud-based data solutions on Azure or Google Cloud to ensure scalable and efficient data storage and processing.
• Leverage Apache tools, including Airflow, Spark, and Hadoop, for orchestrating data workflows and processing large datasets.
• Write and maintain high-quality code in programming languages such as Java, Python, or C#.
• Implement real-time data streaming and event-driven architectures using technologies like Apache Kafka or Azure Service Bus.
• Mentor and guide a team of data engineers, fostering a culture of collaboration and continuous improvement.
• Ensure adherence to data governance and data quality best practices to maintain data integrity and reliability.
• Analyze and optimize current database architecture to enhance performance and scalability.
• Tune SQL queries and ETL processes to improve data performance and efficiency.
• Collaborate with cross-functional teams to understand data requirements, design scalable data solutions, and ensure data security.
• Implement Dev Ops practices and tools for CI/CD in data engineering to streamline development and deployment processes.
• Demonstrate strong analytical and problem-solving skills while paying attention to detail.

• Bachelor’s degree in computer science, Data Engineering, or a related field.
• 5+ years of experience in data engineering, with a strong focus on developing and maintaining data pipelines and ETL processes.
• Proficient in Microsoft SQL Server and SSIS stack for data management tasks.
• Expertise in designing and managing cloud-based data solutions on Azure or Google Cloud.
• Experience with Apache tools, including Airflow, Spark, and Hadoop.
• Strong programming skills in Java, Python, or C#.
• Experience with real-time data streaming and event-driven architecture, such as Apache Kafka or Azure Service Bus.
• Strong leadership skills with a demonstrated ability to mentor and guide a team of engineers.
• Knowledge of data governance and data quality best practices.
• Proven ability to optimize current database architecture for enhanced performance and scalability.
• Excellent analytical and problem-solving skills with a keen attention to detail.
• Strong communication skills to convey technical concepts effectively to non-technical stakeholders.

• Experience with machine learning and data analytics tools is a plus.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) for presenting data insights.
• Knowledge of Agile methodologies and experience working in an Agile environment.