Qualifications:

• Proven experience as a Data Engineer, with at least 5+ years in a leadership role.
• Strong proficiency in DBT, AWS Glue, and AWS Postgres.
• Experience with cloud platforms (e.g., AWS) and data warehousing solutions.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders.
• Knowledge of SDLC processes.
• Proficient with CI/CD tools and methodologies.
• Experience with automated code testing tools and techniques.
• Familiarity with Agile and Scrum development methodologies.
• Excellent organizational and time management skills, and the ability to handle multiple projects.

Preferred Qualifications:

• Experience with machine learning and data science workflows.
• Familiarity with DevOps practices and tools (e.g., Docker, Kubernetes, CI/CD pipelines).
• Certification in cloud platforms or data engineering.

Key Responsibilities:

• Lead and mentor a team of data engineers, providing guidance and support to ensure high performance and professional growth.
• Design, develop, and maintain scalable data pipelines and ETL processes to support data integration and analytics.
• Collaborate with cross-functional teams to understand data requirements and deliver data solutions that meet business needs.
• Ensure data quality, integrity, and security by implementing best practices and monitoring data processes.
• Optimize and tune data systems for performance and scalability.
• Develop and maintain documentation for data processes, systems, and workflows.
• Stay up-to-date with the latest industry trends and technologies in data engineering and analytics.
• Implement and manage continuous delivery systems and methodologies on AWS.
• Design and maintain automated deployment systems.
• Recommend process improvements to ensure system scalability and reliability.
• Support development and maintenance of CI/CD processes for application deployments.
• Manage, monitor, and optimize automation tools for deployment, monitoring, and operations.
• Troubleshoot and resolve issues in development, testing, and production environments.

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