Senior Database Engineer | US

Degreed • Full-time • Hybrid in Utah, United States • 1d ago

Fast Facts

Join Degreed as a Senior Database Engineer, where you'll design and manage robust data solutions that support critical applications and insights, ensuring they are scalable and reliable.

Responsibilities: Key responsibilities include designing and optimizing SQL Server databases, managing production stability, ensuring database quality, building reliable data pipelines, and collaborating with engineering teams.

Skills: Required skills include expertise in SQL Server, database performance mechanics, cloud database architecture (Azure), and familiarity with AI tools for database management.

Qualifications: Preferred qualifications include strong experience in relational data modeling, performance optimization, and database change management in production environments.

Location: Hybrid role based in Utah, US; requires one day a week in the office.

Compensation: Not provided by employer. Typical compensation ranges for this position are between $120,000 - $160,000.

At Degreed, we help organizations build the skills they need to adapt, grow, and stay competitive. As a Senior Database Engineer, you’ll play a critical role in making that possible by designing, scaling, and operating the data foundations that power business-critical applications and insights across our platform.

This role exists to ensure our databases are performant, reliable, and built for long-term evolution as Degreed continues to grow. You’ll partner with engineering, product, and platform teams, including one day a week working from our Utah office, to turn complex requirements into durable data solutions that customers can trust.

Key Skills

Deep understanding of relational data modeling concepts: Knowledge of normalization, denormalization, indexing strategies, and schema evolution patterns in SQL Server, applied to systems that grow in scale and complexity over time.
Strong grounding in SQL Server performance mechanics: Understanding of query execution plans, indexing behavior, locking, concurrency, and resource usage, with the ability to reason about root causes of performance issues.
Experience managing database change risk in production environments: Familiarity with schema versioning, backward-compatible changes, data migrations, and rollback strategies in systems with live traffic and uptime requirements.
Working knowledge of cloud-based database architectures on Azure: Understanding of how availability, backups, recovery, scalability, and cost trade-offs work when operating SQL Server in Azure-hosted environments.
Knowledge of database code quality and design standards: Familiarity with best practices for secure, maintainable database and data-access code, including review criteria, naming conventions, and design trade-offs.
Ability to leverage AI tools and technologies relevant to the role: Experience using AI-assisted tools for query analysis, troubleshooting, optimization suggestions, or technical documentation to support database engineering workflows.

Key Responsibilities

Design, evolve, and optimize SQL Server databases at scale: Create schemas, queries, stored procedures, and indexing strategies, and continuously refactor them to improve performance, reliability, and long-term maintainability in production systems.
Own database changes and production stability: Plan, deploy, and validate schema and data changes with minimal downtime, clear rollback strategies, and hands-on response to performance, availability, and scalability incidents.
Ensure database quality through reviews and testing: Lead database code reviews and maintain acceptance tests that validate correctness, performance, and reliability before changes reach production.
Build and operate reliable data pipelines: Develop and maintain data flows between systems, ensuring data quality, consistency, and observability across environments.
Partner with engineering and product to enable features: Collaborate with backend and frontend engineers, product managers, and designers to translate product needs into scalable data models, APIs, and user-facing capabilities.
Apply Elasticsearch where it adds value: Support search, analytics, or observability use cases by combining Elasticsearch with relational data stores when appropriate.
Document and align database practices across the platform: Maintain clear documentation of database architecture and standards, and align database strategies with platform, security, and reliability initiatives.

Compensation

We are committed to fair and equitable compensation practices.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to: skill set, depth of experience, certifications, specific work location, and internal equity.