Senior Database Engineer

The Database Engineer will be working closely with development teams during the design, development, testing and implementation of in-house application code primarily supporting their data storage and data access needs. While the focus will be on SQL Server, expertise in MongoDB, Elasticsearch and other DBMS platforms is crucial in supporting our ability to modernize and grow. The goal of this role is to be more proactive by addressing database performance and stability earlier on in the SDLC.

What You Will be Doing:

• Partner with application development teams to ensure the delivery of robust, data-intensive OLTP applications.
• Provide technical expertise(e.g.schema design, query optimization, indexing, stress testing, etc)in SQL Server, MongoDB, Elasticsearch, and other DBMS platforms.
• Assist in understanding and implementing the proper database platform based on data storage, data retrieval, and availability requirements.
• Create and enforce database standards pertaining to nomenclature, security, and access methods (paging, caching, etc).
• Conduct performance/stress testing in partnership with App Dev and Performance Engineers.
• Identify and translate the data needs of development teams into structured requests ensuring timely delivery.
• Ad hoc troubleshooting of database related issues in non-prod.
• Liaise with the Database Administration team to guarantee the infrastructure can support current and future application development.

• Bachelor’s degree or higher is preferred or relevant work experience.
• Exceptional aptitude for learning new tools/technologies.
• Excellent verbal and written communication skills.
• Experience with ORMs such as Entity Framework.
• 3 to 5years of professional experience using SQL Server or other relational database platforms.
• 1 to 3years of professional experience using MongoDB, Elasticsearch or other NoSQL database platforms.
• Knowledge of database design principles, data modeling, and normalization.
• Familiarity with containerization/orchestration tools (e.g., Docker, Kubernetes, Tilt).
• Familiarity with DevOps practices and tools (e.g.git, Azure Devops, Pipelines).
• Experience with scripting languages (e.g.Python, PowerShell) for automation tasks.
• Exposure to and understanding of AI models to accelerate growth (e.g. Custom skills, tool sets,etc)
• In-depth knowledge of performance-tuning queries and optimizing indexes.