Senior Manager, Data Operations

Medical Guardian•Philadelphia, PA

3d•Onsite

About The Position

Medical Guardian is a fast-growing digital health and safety company on a mission to help people live a life without limits. With 14 consecutive years on the Inc. 5000 list of Fastest Growing Companies, we are redefining what it means to age confidently and independently. We support over 625,000 members nationwide with life-saving emergency response systems and remote patient monitoring solutions. Trusted by families, healthcare providers, and care managers, our work is powered by a culture of innovation, compassion, and purpose. The Senior Manager of Data Operations leads the organization's Data Operations function and ensures that enterprise data services, reporting capabilities, and operational processes are reliable, governed, secure, and aligned with business priorities. The role establishes the operating model, service expectations, and continuous-improvement direction and advises technology and business leadership. The Senior Manager will lead a team of individual contributors supporting the organization's current data warehouse, dbt models, business reporting, data quality processes, and operational analytics. As the company's data architecture and platforms evolve, the Senior Manager will partner closely with Data Engineering to maintain continuity, quality, documentation, and effective business support. The Senior Manager will serve as the primary operational bridge between business stakeholders and Data Engineering, establishing priorities, service levels, governance practices, and measures of success for enterprise data services. Protecting PHI and other sensitive member information remains a critical responsibility. To advance these objectives, the Senior Manager of Data Operations will lead the people, processes, controls, and partnerships needed to deliver reliable and trusted data services.

Requirements

Strong understanding of modern data warehousing and lakehouse concepts, dbt, dimensional data modeling, semantic layers, and business intelligence delivery.
Ability to assess data-service health, identify operational and data-quality risks, understand technical trade-offs, and work effectively with data engineers and architects.
Practical SQL proficiency sufficient to investigate data issues, validate results, understand data models, and evaluate the quality and usability of delivered data products.
Experience establishing automated and operational data-quality controls, including monitoring, alerting, issue triage, ownership, remediation tracking, and reporting.
Experience applying service-management practices to data products, including service levels, incident management, problem management, change coordination, root-cause analysis, and continuous improvement.
Strong knowledge of data governance, metadata, lineage, access control, privacy, retention, and secure data-handling practices in a regulated environment.
Working knowledge of Git-based version control, CI/CD, automated testing, orchestration, and observability concepts as they apply to analytics engineering and data pipelines.
Experience with reporting and visualization platforms such as Power BI or Tableau, including the governance and adoption of curated dashboards and reporting assets.
Experience with cloud-based data platforms; experience with Azure, Databricks, dbt, or comparable technologies is preferred.
Working knowledge of HIPAA requirements and methods for protecting PHI and other sensitive member data, including least-privilege access, masking or de-identification, auditability, and secure handling throughout the data lifecycle.
Bachelor's degree in Data Science, Analytics, Computer Science, Information Systems, or a related field, or equivalent practical experience; a master's degree is preferred.
8+ years of experience in data operations, analytics, business intelligence, data management, or a related environment, including progressively responsible technical, operational, and leadership responsibilities.
4+ years of direct people-leadership experience, including coaching, performance management, team development, capacity planning, and delivery accountability.
Demonstrated experience managing business-facing data services, reporting operations, data quality, service levels, incidents, priorities, and stakeholder expectations.
Experience overseeing dbt-based analytics or data-modeling work and leading data operations through changes in platforms, architecture, team responsibilities, or operating models.
Strong ability to guide and mentor data analysts, analytics engineers, report developers, or similar data professionals while partnering effectively with data engineers, data scientists, and architects.
Demonstrated success translating organizational objectives into practical data-service priorities, operating processes, and measurable outcomes.
Excellent leadership, written and verbal communication, stakeholder-management, problem-solving, and critical-thinking skills.

Nice To Haves

Experience in healthcare and/or retail is a plus
Experience operating in a regulated, compliance-driven environment such as HIPAA, SOC 2, or PCI DSS is strongly preferred.

Responsibilities

Lead, coach, and develop Data Operations individual contributors while establishing the team's operating model, service roadmap, priorities, standards, measures of success, and continuous-improvement direction.
Own portfolio intake, capacity planning, prioritization, coordination, and status communication for business reporting, dashboard, and operational data requests, balancing business value, risk, urgency, and available resources.
Oversee the operational management of the organization's data warehouse and dbt-based modeling processes, ensuring reliable delivery, documentation, quality, and support.
Serve as the senior operational representative for Data Operations and business-service requirements in data architecture and platform discussions, influencing priorities and operating decisions with Data Engineering and Enterprise Architecture.
Partner with Data Engineering to establish clear operational and technical ownership for data products, models, pipelines, documentation, quality controls, lineage, and ongoing support.
Translate business needs into clear requirements, priorities, acceptance criteria, and operational expectations for Data Engineering and other technology partners.
Establish and monitor service-level objectives for critical reports, dashboards, datasets, and operational data processes, including availability, freshness, completeness, accuracy, and delivery timeliness.
Coordinate data incident response, stakeholder communication, root-cause analysis, corrective actions, and follow-through for data-service failures and recurring quality issues.
Maintain an inventory of critical data products, business owners, technical owners, dependencies, authoritative sources, lineage, and service expectations.
Partner with business stakeholders to define and govern key performance indicators, semantic definitions, and trusted reporting sources, reducing duplicate or conflicting metrics and data models.
Oversee business reporting and visualization practices so complex information is communicated clearly and consistently to executive and functional stakeholders, including Finance, Marketing, Operations, and other business areas.
Coordinate business acceptance testing and validation for new or materially changed data products, reports, dashboards, and operational processes.
Develop and manage data governance and operating procedures in partnership with Security, Privacy, Compliance, Data Engineering, and Enterprise Architecture, including data quality, access, documentation, lineage, retention, and secure handling of PHI and other sensitive data.
Provide executive-level reporting on Data Operations performance, business impact, risks, capacity, and priorities, including reliability, data quality, incident trends, delivery time, backlog health, and adoption of trusted reporting assets.
Manage relationships with external data vendors, partners, and consultants as needed.