Sr. Database Administrator

We're looking for an experienced Senior Database Administrator to join the team at FinQuery. You should be highly proficient with schema design, indexing, advanced query tuning, and database architecture. Beyond deep technical expertise, we are looking for a seasoned professional with strong mentorship and knowledge-sharing capabilities to elevate the entire engineering team. We also value leaders who integrate AI tools into their daily workflows to drive efficiency. Whether you built those habits through professional experience, technical leadership, or continuous self-study, we'd love to talk.

We run Agile with Kanban, and we believe in continuous improvement in our systems, our tools, and how we work together. In this role, you'll lead hands-on PostgreSQL administration on AWS, solve complex query performance challenges, guide data architecture strategy, and mentor junior and mid-level engineers. You'll collaborate closely with engineering leadership while leveraging AI-driven approaches to optimize workflows and scale infrastructure efficiently.

How You'll Make an Impact:

• Help administer and monitor AWS PostgreSQL databases, picking up best practices for reliability and performance along the way

• Lead performance optimization efforts, spot complex database bottlenecks, and implement advanced tuning solutions

• Collaborate daily with development teams and other departments since communication is a big part of this job

• Review and approve developer-driven data architecture changes, establishing guidelines and providing structured feedback

• Dig into query performance problems and grow your skills in database optimization

• Take part in release and deployment processes, getting real exposure to production workflows

• Contribute to internal improvements like automating manual tasks, speeding up data delivery, and supporting infrastructure growth

• Use AI agents, LLM-powered tools, and automation to handle routine work like query analysis, schema reviews, documentation, and troubleshooting more efficiently

• Keep RDS systems running well day to day

• Help assess and improve data schemas for efficiency by reviewing indices, spotting redundant columns, and evaluating table structures

• Stay curious, research new technologies, propose AI-driven solutions, and bring ideas to make our systems and team more productive

• Actively mentor junior and mid-level engineers, fostering technical growth, establishing best practices, and driving knowledge-sharing across teams

The Expertise You'll Bring:

• A solid foundation in relational databases and data architecture built through professional work, school projects, internships, or personal exploration

• Experience or strong academic exposure to designing, building, and scaling databases

• Familiarity with SQL and a real interest in going deeper with PostgreSQL and cloud database services

• Comfort using AI assistants, copilots, and LLM-powered tools as a core part of how you work, not a novelty you try occasionally

• A team-first mindset where success is defined by what we accomplish together

• A proactive, curious attitude and a genuine desire to keep learning

Preferred Qualifications

• 7-8 years of professional experience as a Database Administrator or Database Engineer managing mission-critical databases

• 7-8 years of experience working with enterprise databases and scalable data architectures

• Hands-on experience with AWS RDS or Aurora

• Demonstrated use of AI agents or LLM-powered tools to do technical work more efficiently

• Demonstrated track record of technical mentorship, team leadership, and cross-functional knowledge sharing

Tech You'll Work With

• Hosting & Administration: AWS RDS and Aurora

• Database Systems: PostgreSQL and MS SQL Server

• Languages: SQL, Python, and Shell Scripting

• AI & Agentic Tools: LLM-powered assistants like Gemini, Claude, and GitHub Copilot, alongside AI-driven automation workflows

• Data Warehouses & Integration: Snowflake, FiveTran, Celigo, and Boomi

• Build & Deployment: GitHub Actions, Terraform, Liquibase, and Jenkins

• Analytics & Logging: DataDog and Power BI

• Communication: Atlassian Jira and Slack