How You'll Make an Impact
Lead the architecture, implementation, and operational management of enterprise database platforms, focusing on PostgreSQL (including AWS Aurora) and MS SQL Server.
Own the upgrade program. Plan and execute major-version upgrades across the fleet with minimal downtime, and keep engine versions current enough that they never gate replication or recovery capability.
Raise the bar on schema-change governance - review standards for migrations, index and locking review, and automated guardrails so unsafe changes are caught before they reach production.
Partner with security and compliance on encryption, row-level security, least-privilege access, and the evidence our SOC 1/2 and regulatory obligations depend on.
Be a senior escalation point for database-driven incidents, and turn each one into a durable fix, a runbook, or an alert rather than a repeat.
Build automation and AI-assisted tooling that makes routine database work self-serve for product engineers, and mentor engineers across the org on data modeling, query design, and operating databases at scale.
Perform advanced troubleshooting, root cause analysis, performance analysis, capacity planning, tuning, backup, recovery, and disaster recovery planning.
Establish database monitoring and reliability frameworks while driving IaC adoption with Terraform and integrating CI/CD for automated provisioning, deployments, upgrades, and testing.
Collaborate with software engineering, DevOps, Analytics and product teams to provide architecture guidance, technical consultation, and platform support.
Define and implement database engineering standards, configuration management practices, governance processes, and operational procedures.
Evaluate emerging database technologies by using proof-of-concepts, and modernization initiatives.
Use AI agents, LLM-powered tools, and automation to handle routine work like query analysis, schema reviews, documentation, and troubleshooting more efficiently
Champion Kanban delivery practices, operational excellence, and continuous improvement across database engineering services.
- Mentor engineers and promote engineering excellence through coaching, knowledge sharing, and technical leadership.
- The Expertise You'll Bring:
- At least 7-8 years administering production PostgreSQL, including databases that the business depends on around the clock.
A bachelor’s degree in computer science or a related field, or equivalent practical experience.
Deep expertise in PostgreSQL internals (MVCC, vacuum behavior, replication, and query planning) and query/workload tuning, alongside comfort utilizing AI assistants, copilots, and LLM-powered tools.
Proven experience operating PostgreSQL on AWS RDS/Aurora (instance sizing, parameter groups, monitoring, engine upgrades) and designing/testing high availability and disaster recovery solutions.
Solid Linux administration and scripting in Bash and/or Python.
Experience working within a formal change management process in a regulated, audited or otherwise controlled environment.
The ability to explain database risk and trade-offs clearly to non-technical stakeholders and to senior management.
Authorization to work in the United States.
A team-first mindset where success is defined by what we accomplish together
A proactive, curious attitude and a genuine desire to keep learning
Nice to Have Qualities
Database & Platform Expertise: Experience administering Microsoft SQL Server, containerized PostgreSQL on Kubernetes (persistent storage, backups, failover), and cloud infrastructure automation using Terraform or Ansible.
Modern Data & AI Integration: Proficiency in AI best practices (e.g., Claude) and deploying AI agents to automate database workflows alongside hands-on experience with Snowflake, ElastiCache/Redis, or OpenSearch.
Enterprise Delivery & Compliance: Proven track record supporting large-scale data migrations, platform integrations, and maintaining compliance within audited environments such as SOC 1 or SOC 2.
Tech Stack that 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
