Database Administrator

The role – what you’ll do

Barr is seeking a Database Administrator to join ourMinneapolis, Minnesota, team. In this hybridrole, you will support the Information Systems group and play a key part in managing the performance, integrity, and security of our internal database systems while supporting modernization and AI-readiness initiatives.You’lloversee SQL Server environments, implement and maintain role-based access controls, and establish monitoring and alerting systems to proactively identify and resolve database issues. You’ll also perform routine maintenance, optimization, and backup tasks andcollaborate with cross-functional teams to ensure secure, scalable, and reliable data access across systems.

A successful person in this role has strongproblem-solvingskillsand keen attention to detail formaintaining data integrity and system reliability.They are deadline driven and enjoy using their project management skills, along with their technical expertise, to work collaboratively as part of a cross-functional team.They are also excited to help bridge legacy systems with the evolving demands of data governance, modernization, and scalable data infrastructure.

Your impact – key responsibilities

• Database administration and maintenance:administer and maintain SQL Server environment, perform patching, upgrades, performance tuning, and routine maintenance tasks such as indexing and backups. 

• Security and compliance:design and implement role-based access control (RBAC) to enforce database security. Support data governance and change management practices in alignment with emerging standards and practices.

• Modernization and cloud migration:Support initiatives to transition from legacy systems to modern, cloud-based platforms and improve database structures and workflows.

• Strategic planning:focus on adopting emerging technologies like NoSQL, vector databases, and Azure-native services. Support AI/ML initiatives through data readiness and contribute to high availability and disaster recovery strategies.

About the opportunity

• Compensation:Anticipated range of $80,000–100,000 annually. Compensation will vary based on relevant experience, education, skill level, and other compensable factors. Employees in this position may also be eligible for a discretionary cash bonus based on team and individual performance. This position is classified as exempt under the Fair Labor Standards Act.

• A hybrid work arrangement may be considered for this position. A hybrid work arrangement refers to splitting time worked between a Barr office and a home office. This position is based out of Barr's Minneapolis, Minnesota, office.

About you – required core competencies 

• Education:Bachelor’s degree in computer science, data engineering, information systems, or a related field or equivalent experience

• Experience:Five or more years of relevantexperience.

• Experience managing Microsoft SQL Server in a production environment.

• Proficiencyin T-SQL, query optimization, and database performance tuning.

• Knowledge of cloud-based database services, particularly within the Microsoft Azure ecosystem (e.g., Azure SQL Database, Azure Monitor).

• Experience with SQL Server backup, recovery, and high availability strategies, particularly SQL Server replication.

• Experience configuring and maintaining role-based access control (RBAC) in SQL Server.

• Software/Programs:SQL Server, SQL Server Integration Services (SSIS), Microsoft Azure ecosystem (e.g., Azure SQL Database, Azure Monitor).

• Communication: strong interpersonal, oral, and written communication skills and the ability to communicate effectively with a variety of different people.

• Must be legally authorized to work in the United States without the need for sponsorship by Barr, now or in the future.

Helpful additional experience (not required)

• Experience with NoSQL databases such as MongoDB, Redis, or DynamoDB for managing unstructured or semi-structured data.

• Familiarity with vector databases (e.g., Pinecone, Weaviate, Qdrant, Milvus) or the concept of embedding storage for AI/ML applications.

• Understanding of data architecture patterns used in AI/ML pipelines, including support for retrieval-augmented generation (RAG), chat history storage, or metadata management.

• Exposure to cloud-native database services in Azure.

• Ability to work with JSON-based or schema-less data models and flexible indexing strategies.

• Familiarity with graph databases like Neo4j or Amazon Neptune and their use in knowledge graphs or relationship modeling.

#LI-Hybrid