Data Engineer Iii

Overview

• Drive innovation in data engineering by designing scalable solutions to enhance analytics and decision-making processes.
• Collaborate with cross-functional teams to align data strategies with organizational objectives and goals.
• Lead technical initiatives, mentoring junior engineers and fostering a culture of innovation and excellence.
• Develop and optimize data pipelines using advanced technologies and methodologies to ensure efficiency and reliability.
• Ensure data integrity and reliability through rigorous testing and quality assurance processes.
• Contribute to the modernization of the organization's data infrastructure and platform.
• Utilize cloud services to implement secure and scalable data solutions tailored to business needs.
• Support continuous integration and deployment workflows to enhance development efficiency and agility.

Key Responsibilities & Duties

• Develop and maintain robust data pipelines using industry-standard tools and frameworks to support business operations.
• Implement and optimize ETL/ELT processes for diverse data environments to ensure seamless data flow.
• Create scalable data ingestion frameworks to support complex data methodologies and analytics needs.
• Write and optimize SQL procedures and scripts for efficient data transformations and processing.
• Develop automation solutions using Python and cloud-based tools to streamline workflows.
• Monitor and enhance pipeline performance through continuous improvement strategies and proactive measures.
• Support data modeling and schema evolution to improve database performance and scalability.
• Collaborate on CI/CD processes, ensuring adherence to industry best practices and standards.

Job Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field is required.
• Minimum of 5 years of experience in data engineering or related roles.
• Proficiency in SQL Server, T-SQL, and database management concepts is essential.
• Experience with ETL/ELT tools and methodologies for efficient data processing.
• Familiarity with data warehousing and dimensional modeling techniques.
• Knowledge of cloud services, particularly Azure, for implementing data solutions.
• Proficiency in Python programming for data engineering tasks and automation.
• Understanding of CI/CD practices and tools for streamlined workflows and deployments.