Job Summary:
The AVP Data engineer will support all aspects of data engineering activities, including data design, development, testing, debugging, documentation, deployment, and production support. The individual will apply software engineering methods and techniques to perform code reviews, unit testing, integration testing, and documentation. They will also contribute to technical roadmap planning and work closely with the Lead Software Engineers to ensure timely delivery of new features and maintenance releases.

Responsibilities:

• Lead the development of end-to-end data pipelines including ETL/ELT, data quality, data governance, metadata management, data modeling, and master data management.
• Applies data engineering skills and knowledge of industry standard practices to develop scalable, reliable, fault-tolerant systems and processes that meet business requirements.
• Collaborates with project managers, architects, developers, testers, operations staff, product owners, and end users to analyze business requirements, identify problems, propose solutions, prioritize features, estimate costs and time, and communicate risks and status.
• Maintains awareness of emerging technologies and trends; demonstrates flexibility and willingness to learn new technologies as needed.
• Applies understanding of concepts and procedures within own area and basic knowledge of other areas to resolve issues that have impact beyond immediate area.
• Performs code reviews, unit testing, integration testing, and documentation.
• Collaborates with development team members and customers to troubleshoot and resolve application issues in production environments.
• Utilizes knowledge of system architecture and data models to maintain existing applications and work on new projects.
• Identifies opportunities for operational improvements and efficiency gains.

Requirements:

• Bachelor’s degree in Computer Science or related field; Master’s degree preferred
• Experience working in Agile/Scrum environment
• Ability to understand complex technical specifications and translate into functional code

• Lead the development of end-to-end data pipelines including ETL/ELT, data quality, data governance, metadata management, data modeling, and master data management.
• Applies data engineering skills and knowledge of industry standard practices to develop scalable, reliable, fault-tolerant systems and processes that meet business requirements.
• Collaborates with project managers, architects, developers, testers, operations staff, product owners, and end users to analyze business requirements, identify problems, propose solutions, prioritize features, estimate costs and time, and communicate risks and status.
• Maintains awareness of emerging technologies and trends; demonstrates flexibility and willingness to learn new technologies as needed.
• Applies understanding of concepts and procedures within own area and basic knowledge of other areas to resolve issues that have impact beyond immediate area.
• Performs code reviews, unit testing, integration testing, and documentation.
• Collaborates with development team members and customers to troubleshoot and resolve application issues in production environments.
• Utilizes knowledge of system architecture and data models to maintain existing applications and work on new projects.
• Identifies opportunities for operational improvements and efficiency gains