Analytics Engineering Manager - Lead Data Assets (Hybrid/Remote)

PatientPoint, Inc.; Cincinnati, Northern (OH, KY); Hybrid; USD 120,000 - 150,000; Full time

Job summary

PatientPoint, Inc. is seeking a Manager of Analytics Engineering in the Cincinnati/NYC area or remote within the Eastern Time Zone.

The role leads a team responsible for transforming raw data into governed, reusable analytics assets, including managing dbt models, semantic layers, and BI frameworks to deliver trusted, self-service insights. The position requires hands-on expertise in modern analytics engineering practices, close collaboration with Data Engineering, Reporting, and Analytics

Responsibilities

• Lead, manage, and train a team of data visualization engineers and professionals.
• Oversee resource allocation, prioritization, and project delivery to ensure high-quality outcomes within deadlines.
• Provide mentorship and guidance to team members, cultivating accountability, collaboration, and growth.
• Contribute to frameworks, methodologies, and tools that improve how the company designs and delivers reliable data assets.
• Develop and implement analytics engineering strategies aligned with business objectives, focusing on scalable, automated solutions.
• Collaborate with Data Engineering, Reporting, Analytics teams to ensure data pipelines, tools, and dashboards meet business needs.
• Own and evolve the company’s analytics engineering ecosystem, including dbt, Snowflake, and Looker.
• Define standards for modeling, testing, documentation, and version control in dbt and BI layers.
• Partner with stakeholders to establish and maintain a governed core metrics set.
• Champion self-service enablement to ensure teams access reliable data without bottlenecks.
• Ensure data quality, integrity and compliance with governance standards.

Job description

PatientPoint, Inc. is seeking a Manager of Analytics Engineering in the Cincinnati/NYC area or remote within the Eastern Time Zone.

The role leads a team responsible for transforming raw data into governed, reusable analytics assets, including managing dbt models, semantic layers, and BI frameworks to deliver trusted, self-service insights. The position requires hands-on expertise in modern analytics engineering practices, close collaboration with Data Engineering, Reporting, and Analytics