Manager, Analytics Engineering

PatientPoint®; Philadelphia (Philadelphia County); Hybrid; USD 130,000 - 170,000; Full time

Job summary

PatientPoint® is seeking an Analytics Engineering Manager to lead a team transforming raw data into trusted analytics assets. You will oversee dbt models, semantic layers, and BI frameworks to empower self-service insights that support business priorities.

The role requires hands-on leadership, collaboration with Data Engineering, Reporting, and Analytics teams, and a focus on scalable, governed data products with measurable impact.

Responsibilities

• Lead, manage, and train a team of data visualization engineers and professionals.
• Foster a culture of continuous learning, innovation, collaboration, and improvement.
• Oversee resource allocation, prioritization, and project delivery to ensure high-quality outcomes within deadlines.
• Provide mentorship and guidance to team members, cultivating a culture of accountability, collaboration, and growth.
• Contribute to the development of 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 with a focus on repeatable, scalable, and automated solutions.
• Ensure the accuracy, consistency, and reliability of all data assets.
• Collaborate with Data Engineering, Data Reporting, Data Analytics, and Advanced Analytics teams to ensure data pipelines, tools, and dashboards for robust reporting meet business needs.
• Own and evolve the company’s analytics engineering ecosystem, including shared ownership of dbt, Snowflake, and Looker.
• Define and enforce standards for modeling, testing, documentation, and version control in dbt and BI layers.
• Partner with stakeholders to establish and maintain a governed set of core metrics.
• Champion self-service enablement, ensuring teams can access reliable data without bottlenecks.
• Ensure data quality, integrity and compliance with industry standards and the company’s Data Governance standards.
• Own the standardization of the company’s metric layer to ensure consistent definitions across BI tools.

Job description

Join PatientPoint to be part of a dynamic team creating change in and around the doctor's office. As a leading digital health company, we innovate to positively impact patient behaviors. Our purpose-driven approach offers an inspirational career opportunity where you can contribute to improving health outcomes for millions of patients nationwide.

Location: Cincinnati, OH (Hybrid); New York, NY (Hybrid) ; or remote within the Eastern Time Zone.

Travel Requirements: 3 to 5 times per year

Job Summary

The Manager of Analytics Engineering will lead a team responsible for transforming raw data into governed, reusable, and scalable analytics assets. This includes managingdbtmodels, semantic layers (LookML), and BI frameworks that empowerthecompanywith trusted, self-service insights.The role requires hands-on expertise in modern analytics engineering practices, close collaboration with Data Engineering, Reporting,and Analytics teams, and the ability to align data products with business priorities.

What You’ll Do

• Lead,manage, andtraina team ofdata visualization engineersand professionals.
• Foster a culture of continuous learning,innovation, collaboration, and improvement.
• Oversee resource allocation, prioritization, and project delivery to ensure high-quality outcomes within deadlines.
• Provide mentorship and guidance to teammembers,cultivatinga culture of accountability, collaboration, and growth.
• Contribute to the development of frameworks, methodologies, andtools that improve howthe companydesigns and delivers reliable data assets.

Data Strategy and Execution:

• Develop and implementanalyticsengineeringstrategies aligned with business objectives with a focus on repeatable, scalable, and automated solutions.
• Ensure the accuracy, consistency, and reliability of alldata assets.
• Collaborate with Data Engineering, DataReporting, Data Analytics,and Advanced Analytics teams to ensure data pipelines, tools,and dashboards for robust reporting and analytics meet the needs of the business.
• Own and evolvethe companiesanalytics engineering ecosystem, includingshared ownership ofdbt, Snowflake, and Looker.
• Define and enforce standards for modeling, testing, documentation, and version control indbtandBI layers.
• Partner with stakeholders to establish and maintain a governed set of core metrics.
• Champion self-service enablement, ensuring teams can access reliable data without bottlenecks.
• Ensure data quality, integrity and compliance with industry standards and regulationsandthe companiesData Governance standards.
• Own the standardization ofthe companiesmetric layer to ensure consistent definitions across all BI tools and reports.

Business Impact:

• Partner withbusiness stakeholders and data teams, defining clear requirements, setting expectations, and communicating effectively and efficiently.
• Ensure business requirements are appropriately translated into technical specifications that