Senior Manager, Data Analytics Enablement

Labcorp•Durham, NC

About The Position

The Senior Manager, Data Analytics Enablement leads solution design, architecture reviews, technical governance, and end-to-end delivery for enterprise data, analytics, reporting, and AI initiatives. The role partners with business stakeholders and technology teams to translate requirements into scalable solutions, guiding development of cloud-based data platforms using technologies such as Snowflake, Databricks, and AWS. It establishes practices for data engineering, governance, quality, security, and support; advances AI-assisted engineering and AI-Driven Development Lifecycle practices; and evaluates emerging technologies through proof-of-concept initiatives. The position advises business and technology leaders on data, analytics, AI, and enterprise platform strategy, and supports executive reporting, business intelligence, analytics, and data-driven decisions. It manages technical risks, dependencies, and delivery challenges while coordinating with enterprise architecture, infrastructure, security, and operations teams. The role leads, coaches, and develops Data Engineers, Analytics Engineers, and other technical professionals, with responsibility for workforce planning, capacity, resource allocation, utilization, performance management, and succession planning. Within Labcorp Diagnostics Operations, the Senior Manager supports and delivers business intelligence to senior executives and operational leaders. The role uses analytical tools to streamline and automate data management, analysis, reporting, and visualization, providing leaders with actionable insights into Diagnostics Operations supply-chain health. It manages resources related to business process analytics and reporting on esoteric business-unit performance. This is a full-time, exempt salaried position on a First Shift schedule, with standard business hours Monday through Friday, 8:00 a.m. to 5:00 p.m. Business needs may occasionally require flexibility, including earlier, later, or additional hours, with reasonable notice when possible.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
12 or more years of experience in Data Engineering, Data Warehousing, Analytics, or related technology domains.
5 or more years of experience leading and managing technical teams, including performance management, coaching, and talent development.
5 or more years of experience in data analytics.
5 or more years of experience with database administration, application program development, SQL development on multiple platforms, and report development or generation.
Proven experience delivering enterprise-scale data, analytics, and reporting solutions using Snowflake, Databricks, AWS, and modern cloud technologies.
Strong expertise in Data Engineering, Data Warehousing, Data Modeling, ETL/ELT frameworks, Data Governance, and Analytics platforms.
Experience leading solution architecture reviews, technical design governance, and large-scale implementation programs.
Strong understanding of Data Lake, Lakehouse, and modern cloud-based data platform architectures.
Hands-on experience with Python, PySpark, Spark, SQL, and enterprise data integration tools.
Experience with business intelligence and visualization platforms such as Power BI, Tableau, or similar technologies.
Experience leveraging AI-assisted development tools and implementing AI-driven engineering practices.
Strong knowledge of Agile delivery methodologies, DevOps, CI/CD practices, and cloud-native solution development.
Excellent stakeholder management, communication, leadership, and problem-solving skills.
Experience in Healthcare, Diagnostics, Life Sciences, or Pharma.
Good database-handling knowledge and proficiency in SQL, including experience with Toad/Today Data Point® for Oracle or an equivalent.
Experience developing auto-generated reports, such as SQL Server Report Services or Telerik Reporting.
Excellent PC skills, including MS Word, Excel, PowerPoint, and Access.

Nice To Haves

5 or more years of experience with Tableau and Alteryx.
SQL certification and Tableau certification.
Six Sigma or Lean certification or experience.
Experience in rapid application development.
Experience developing a hands-off approach to generating and delivering complex informational reporting.

Responsibilities

Lead solution design, architecture reviews, and technical governance for enterprise data, analytics, reporting, and AI initiatives.
Partner with business stakeholders, product owners, project managers, and architects to translate business requirements into scalable technology solutions.
Oversee end-to-end enterprise solution delivery, ensuring quality, security, scalability, and alignment with business objectives.
Guide teams in designing and implementing cloud-based data platforms using technologies such as Snowflake, Databricks, and AWS.
Establish and enforce best practices for data engineering, governance, quality, security, and operational support.
Drive adoption of AI-powered engineering tools and AI-Driven Development Lifecycle practices across design, development, testing, deployment, and support.
Evaluate emerging technologies and lead proof-of-concept initiatives to improve platform capabilities and delivery efficiency.
Coordinate with enterprise architecture, infrastructure, security, and operations teams to align with enterprise standards.
Manage technical risks, dependencies, and delivery challenges to support successful project outcomes.
Support executive reporting, business intelligence, analytics, and data-driven decision-making initiatives.
Advise business and technology leadership on data, analytics, AI, and enterprise platform strategy.
Lead, coach, mentor, and develop teams of Data Engineers, Analytics Engineers, and other technical professionals.
Drive workforce planning, capacity management, resource allocation, utilization tracking, performance management, and succession planning.
Foster innovation, accountability, continuous learning, and engineering excellence.
Deliver business intelligence to senior leaders and operational stakeholders within Labcorp Diagnostics Operations.
Use analytical tools to streamline and automate data management, data analysis, reporting, and data visualization.
Provide business leaders with actionable insights into the health of the Diagnostics Operations supply chain.
Manage resources related to business process analytics and report on esoteric business-unit performance.
Work with management and staff to understand day-to-day business operations and requirements, and provide streamlined reporting that supports operational procedures.
Develop auto-generated reports and hands-off processes for generating and delivering complex informational reporting.