Product Management

Position Overview

We are seeking a highly experienced Senior Database Administrator (Senior DBA) to own, operate, and scale cloud-based database platforms for a US Healthcare Revenue Cycle Management (RCM) product ecosystem. This role is accountable for availability, reliability, performance, security, compliance, and cost governance of SQL Server and Snowflake running on cloud platforms (AWS, Azure, GCP).

The Senior DBA will support a microservices-driven architecture integrated with AI/ML, GenAI, Agentic AI, RPA, EDI, telecom-enabled workflows, and real-time payer integrations. This is a production-critical role requiring deep operational ownership in a HIPAA-regulated, audit-intensive healthcare environment.

Job Roles & Responsibilities

Database Platform Ownership (Cloud & On-Prem Hybrid):

• Own end-to-end administration of SQL Server and Snowflake across development, QA, staging, and production environments.
• Manage cloud-hosted database deployments using AWS, Azure, or GCP, including networking, security, and scaling considerations.
• Define and enforce database standards, naming conventions, version control, backup policies, and lifecycle management.
• Lead capacity planning, performance forecasting, and cost optimization, especially for Snowflake warehouses and cloud storage.
• Drive database modernization initiatives aligned with cloud-native and microservices architectures

High Availability (HA), Disaster Recovery (DR) & Performance Engineering:

• Architect, implement, and maintain HA and DR strategies, including:
  • SQL Server Always On, clustering, replication
  • Backup, restore, point-in-time recovery
  • Snowflake replication, failover groups, and recovery strategies
• Ensure business continuity and zero/near-zero data loss for mission-critical RCM workflows.
• Lead performance tuning and optimization for:
  • High-volume transactional workloads (claims, payments, collections)
  • Analytical and reporting workloads
  • AI/Agent-driven batch and real-time processes
• Proactively identify and mitigate performance risks, capacity constraints, and failure scenarios

Microservices, Integration & Data Flow Governance:

• Govern database usage patterns for microservices-based applications, REST APIs, and event-driven architectures.
• Ensure transactional integrity, idempotency, and data consistency across distributed systems.
• Support and validate database interactions for:
  • AI / Agentic AI decision workflows
  • RPA bots and automation pipelines
  • EDI integrations with payers, clearinghouses, and partners
• Partner with engineering teams to ensure data contracts, schema evolution, and backward compatibility

Snowflake & Cloud Data Platform Leadership:

• Own Snowflake platform architecture, including:
  • Warehouses, databases, schemas
  • Tasks, streams, secure views
  • Data sharing and role-based access
• Drive Snowflake cost governance, workload isolation, and performance optimization.
• Support AI/ML, GenAI, and Agentic AI pipelines using Snowflake as a central analytics and data platform.

Enable secure reporting and analytics for Claims, Prior Authorization, Scheduling, Coding, Collections, Payments, and EDI

Security, Compliance & Audit Readiness:

• Enforce HIPAA, SOC 2, and internal security standards across all database environments.
• Own PHI protection mechanisms, including:
  • Encryption at rest and in transit
  • Data masking, tokenization, and anonymization
  • Role-based access control (RBAC) and least-privilege access
• Maintain comprehensive audit trails, logging, and monitoring for regulatory compliance.
• Actively support internal, external, and customer audits, partnering with security and compliance teams

Operational Excellence, Automation & DevOps:

• Implement monitoring, alerting, and automated remediation for database health and performance.
• Define and maintain runbooks, SOPs, and incident response playbooks.
• Drive CI/CD and DevOps best practices for database schema and configuration changes.
• Reduce manual effort through automation, scripting, and proactive governance.

Leadership, Mentorship & Cross-Functional Collaboration

• Mentor and guide DBAs, SQL Developers, and Data Engineers on best practices.
• Lead production readiness reviews, release approvals, and risk assessments.
• Serve as the final escalation point for database-related production incidents.
• Collaborate closely with Engineering, QA, AI/ML, RPA, DevOps, Security, and Product teams.

Candidate Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• 8–12+ years of experience in database administration, with 4+ years in a senior or lead DBA role.
• Strong hands-on experience administering SQL Server and Snowflake in cloud environments.
• Proven experience supporting cloud-native, microservices-based platforms.
• Experience in US Healthcare, RCM, financial systems, or other regulated industries preferred.
• Exposure to AI/ML, GenAI, Agentic AI, and RPA-driven systems is a strong advantage.

Technical Expertise:

• Databases: SQL Server, Snowflake, T-SQL
• HA & DR: Always On, clustering, replication, backup & recovery strategies
• Cloud Platforms: AWS, Azure, GCP (cloud networking and security awareness)
• Microservices & Integrations: REST APIs, Kafka, RabbitMQ
• EDI: 837, 835, 270/271, 276/277, 278
• Security & Compliance: HIPAA, SOC 2, PHI masking, encryption, audit logging
• Monitoring & Automation: Cloud monitoring tools, alerting, CI/CD for DB changes

Skillset:

• Deep expertise in production database reliability, scalability, and performance engineering.
• Strong understanding of distributed systems and microservices data patterns.
• Excellent troubleshooting, decision-making, and incident management skills.
• Strong leadership and mentoring capability.
• Compliance-first mindset with a strong sense of ownership and accountability.

Strategic Impact:

• Ensure high availability, data integrity, and regulatory compliance for mission-critical RCM systems.
• Enable AI/Agentic AI and RPA-driven automation through stable and governed data platforms.
• Minimize downtime, production risk, and audit findings.
• Support long-term cloud scalability and platform modernization initiatives.

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