Sr. Data Engineer; Hybrid

Overview

Position Summary The Senior Data Engineer is a pivotal leader in the team, responsible for spearheading the implementation and maintenance of advanced data products that enable effective data movement and transformation across integrated systems. With extensive expertise in technologies associated with the enterprise data warehouse, this role ensures optimal efficiency in data processing, storage, and retrieval. Acting as a key contributor to major data-driven initiatives, the Senior Data Engineer also plays a vital mentorship role, guiding mid-level and associate staff to enhance the team's overall capabilities and foster a culture of continuous learning and development.

This position is not eligible for sponsorship at this time.

About The Work Unit

Vanderbilt University Information Technology is a human-centric organization that advances our university by delivering innovative solutions and frictionless experiences through collaboration.

• Leadership in Data products Implementation
• Lead the design and implementation of innovative data products for data movement and transformation in complex systems.
• Collaborate with stakeholders to understand business needs and translate them into effective data architecture and data products.

• Data Optimization and Performance Monitoring
• Ensure optimal data processing, storage, and retrieval by establishing and monitoring key performance indicators (KPIs) for data products.
• Identify areas for enhancement and implement strategies to optimize data workflows and operations, improving overall system efficiency.

• Strategic Project Involvement
• Take a proactive role in managing and contributing to key data-driven initiatives and projects, ensuring alignment with organizational goals and objectives.
• Facilitate the deployment of new technologies and methodologies to advance the organization’s data capabilities.

• Mentorship and Team Development
• Mentor and provide guidance to mid-level and associate data staff, improving their technical skills and knowledge in data products and best practices.
• Foster an environment of collaboration and knowledge sharing within the team, encouraging professional development and innovation.

• Quality Assurance and Documentation
• Oversee quality assurance processes for data products, ensuring adherence to standards and compliance requirements.
• Maintain detailed documentation of data architectures, processes, and methodologies for future reference and training purposes.

On-call Responsibilities

The position includes rotating on-call duties for after-hours incident response and requests.

Supervisory Relationships

This position does not have supervisory responsibility. This position reports administratively and functionally to the Data Engineering Manager.

• Bachelor’s degree or equivalent, related experience necessary
• Minimum of 5 years of U.S. based industry experience is necessary
• Bachelor s degree in computer science, Information Technology, Data Science, or a related field preferred
• At least one relevant industry certification (e.g., Snow Pro Core, Microsoft Certified: Azure Data Engineer Associate, AWS Certified Data Analytics, or similar) necessary

• 5-7 years of related experience necessary
• Demonstrated commitment to VUIT’s Guiding Principles is necessary
• Expert-level proficiency in SQL and experience with data modeling and complex queries necessary
• Strong familiarity with ETL processes, data integration tools, and data warehousing technologies using Snowflake Data Cloud necessary
• In-depth knowledge of big data technologies and cloud data platforms (e.g., AWS, Azure, Google Cloud) necessary
• Proven track record in optimizing data pipelines and improving data management efficiency necessary
• Excellent analytical and problem-solving abilities, with experience troubleshooting complex data issues necessary
• Strong leadership and interpersonal skills, with the ability to mentor and develop junior team members necessary
• Effective communication skills, capable of conveying technical concepts to both technical and non-technical stakeholders necessary