Data Engineer Iii

Overview

• Drive impactful data engineering initiatives to enhance analytics and decision-making processes across the organization.
• Collaborate with cross-functional teams to align data strategies with business objectives and deliver innovative solutions.
• Lead technical projects, mentoring junior engineers and fostering a culture of excellence and innovation.
• Design and optimize data pipelines using cutting-edge technologies to ensure efficiency and reliability.
• Implement secure, scalable solutions leveraging cloud services tailored to organizational needs.
• Contribute to the modernization of the data infrastructure, driving organizational growth and agility.
• Support continuous integration and deployment workflows to enhance development efficiency and agility.
• Ensure data integrity and reliability through rigorous testing and quality assurance processes.

Key Responsibilities & Duties

• Develop and maintain robust data pipelines to support business operations and analytics.
• Implement and optimize ETL/ELT processes for seamless data integration across diverse environments.
• Create scalable data ingestion frameworks to support complex methodologies and analytics needs.
• Write and optimize SQL procedures and scripts for efficient data processing and transformations.
• Develop automation solutions using Python and cloud-based tools to streamline workflows.
• Monitor and enhance pipeline performance through proactive measures and continuous improvement strategies.
• 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.