Senior Data Engineer (PostgreSQL DBA)

About the role

M3 Global Research, an M3 company, is hiring a Senior Data Engineer with PostgreSQL DBA expertise to join its data engineering team. The role focuses mainly on database administration tasks such as optimization, performance tuning and security. It is a full-time position, and the company is targeting candidates willing to work US EST hours.

Key responsibilities

• Manage and optimize databases (PostgreSQL, SQL Server, Oracle) for performance, security and availability.
• Design and maintain database schemas, indexes and partitions to support scalability and efficiency.
• Perform database monitoring, backup, recovery and disaster recovery planning.
• Implement security best practices, including access control, encryption and auditing.
• Troubleshoot database performance issues and optimize query performance.
• Ensure compliance with data governance, security policies and industry standards.
• Lead daily standups, prioritize tasks and communicate technical solutions to stakeholders.
• Translate business requirements into data engineering tasks and mentor team members.

Required profile

• Strong PostgreSQL database administration expertise, including performance tuning, security and backup/recovery.
• Excellent communication and leadership skills with technical and non-technical teams.
• Ability to prioritize and manage a team's workload while driving business objectives.
• Problem-solving mindset with strong attention to detail.
• Track record of measurable efficiency gains (faster cycle times, improved stability, less operational toil).

Required skills

• Hands-on experience with modern AI models and developer tooling to speed up software delivery.
• Using AI for PostgreSQL performance tuning, reliability validation, migration planning and runbook automation.
• Applying AI to testing workflows, including test scenario generation, regression coverage and edge-case identification.
• Creating practical automation that reduces manual effort while keeping quality, security and auditability.
• Evaluating AI output quality and using secure patterns for sensitive data.