Position SummaryThe
Manager of Data Platforms & Analytics Engineering is responsible for the architecture, administration, governance, security, reliability, and strategic evolution of enterprise data platforms supporting analytics, AI, data engineering, and business intelligence initiatives.
This leader will serve as the subject matter expert and operational owner for modern data platforms including Databricks, Microsoft Fabric, BigQuery, Synapse, cloud-native databases, and emerging analytics technologies. They will partner closely with data engineering, analytics, AI, governance, and business teams to ensure platforms are secure, scalable, cost-effective, and aligned with enterprise strategy.
The role is also responsible for expanding the technical capabilities of an established Database Administration team, helping experienced SQL Server professionals develop expertise across modern cloud and analytics platforms.
Reporting Relationship Reports to: Director, Data Platforms & Database Services
Key Responsibilities Platform Ownership & Administration - Own the technical administration and operational governance of enterprise data platforms.
- Lead platform configuration, capacity planning, monitoring, backup strategies, disaster recovery planning, and operational support.
- Establish standards for availability, performance, security, reliability, and cost management.
- Develop platform roadmaps and modernization strategies.
- Drive automation wherever possible.
Analytics Platform Architecture - Serve as the lead architect for analytics and data platform technologies.
- Evaluate current platform implementations and recommend improvements.
- Ensure platforms are configured according to industry best practices.
- Define reference architectures and operational standards.
- Lead technology assessments and future platform selection activities.
Security & Data Governance - Establish and maintain access control models.
- Lead platform security reviews and compliance activities.
- Implement role-based access models, data protection controls, and governance standards.
- Partner with Data Trust and Governance teams to support enterprise requirements.
Team Leadership & Capability Development - Mentor and coach database administrators transitioning into modern cloud and analytics platforms.
- Develop training plans and learning paths.
- Build technical depth across Databricks, Fabric, BigQuery, Snowflake, cloud services, and open-source technologies.
- Create a culture of continuous learning and innovation.
Operational Excellence - Establish support models and operational procedures.
- Define platform SLAs, SLOs, and monitoring strategies.
- Create runbooks, standards, and technical documentation.
- Drive incident reduction and platform resiliency improvements.
Stakeholder Engagement - Partner with Data Engineering, Analytics, AI, Governance, Security, Infrastructure, and Application teams.
- Provide consulting and technical direction for platform usage and architecture.
- Communicate platform strategy and recommendations to technical and executive stakeholders.
Required Qualifications Technical Expertise Strong hands-on experience with multiple modern data platforms including:
- Microsoft Fabric (required)
- Azure Data Platform technologies
- Cloud-native analytics platforms
- Data lakehouse architectures
- Data warehousing solutions
- Enterprise identity and security models
Experience in several of the following: Leadership Experience - 7+ years of experience administering enterprise data platforms.
- 3+ years leading technical teams or platform modernization initiatives.
- Experience mentoring engineers and developing technical capabilities.
- Experience establishing operational processes and support models.
Architecture Experience Demonstrated experience with:
- Analytics platform architecture
- Data security and governance
- High availability and disaster recovery
- Platform migrations and modernization projects
Preferred Qualifications - Databricks Certified Professional
- Microsoft Fabric Certification
- Azure Solutions Architect Certification
- Google Cloud Professional Data Engineer
- Experience supporting AI and machine learning workloads
- Experience operating global-scale data environments
