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Program Manager Data Analytics Jobs in Tennessee

Altair Data Resources, Inc

Data Analyst

Brentwood, TN · On-site

You will gain significant experience within our Data Management group helping clients understand more about their data. Using our analytics and visualization tools, you will gain experience working ...

Altair Data Resources, Inc.

Data Analyst

Brentwood, TN · On-site

You will gain significant experience within our Data Management group helping clients understand more about their data. Using our analytics and visualization tools, you will gain experience working ...

Meharry Medical College

Program Manager

Nashville, TN · On-site

The Program Manager oversees the development, operational planning, establishment, execution, and ... Analyze financial data to identify trends, assess project performance, and inform decision-making.

Management Solutions LLC

Program Manager

Knoxville, TN · On-site +1

This role requires the ability to analyze technical direction, client requirements, and project ... Program Management: * Lead and oversee program execution across multiple projects, ensuring ...

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Program Manager Data Analytics information

What is the difference between Program Manager Data Analytics vs Data Analyst?

AspectProgram Manager Data AnalyticsData Analyst
CredentialsBachelor's or Master's in Business, Data Science, or related fields; certifications like PMP or CAPM beneficialBachelor's in Statistics, Data Science, or related fields; certifications like Microsoft Data Analyst Associate helpful
Work EnvironmentOversees multiple projects, collaborates with cross-functional teams, manages stakeholdersAnalyzes data sets, creates reports, supports decision-making within teams
Industry UsageCommon in tech, finance, healthcare, and large organizationsWidely used across industries for data interpretation and reporting

The Program Manager Data Analytics focuses on managing multiple analytics projects and coordinating teams, while Data Analysts primarily analyze data and generate reports. Both roles require strong analytical skills, but the Program Manager has broader responsibilities in project oversight and stakeholder management.

Is 40 too late for data science?

For a Program Manager in Data Analytics, starting a career in data science at age 40 is feasible, as many skills such as statistical analysis, programming, and data visualization can be learned at any age. Experience in related fields and continuous learning through certifications or courses can enhance job prospects regardless of age.

Is AI replacing data analysts?

Program managers in data analytics oversee projects that often involve AI tools, but AI is not replacing data analysts; instead, it automates routine tasks, allowing analysts to focus on complex analysis and strategic insights. Data analysts' skills in interpreting data, storytelling, and domain knowledge remain essential, and proficiency with AI and machine learning tools enhances their effectiveness.

How does a Program Manager in Data Analytics typically collaborate with cross-functional teams?

As a Program Manager in Data Analytics, you will frequently work with data engineers, analysts, business stakeholders, and IT teams to drive analytics initiatives from conception to completion. This collaboration involves translating business objectives into technical requirements, ensuring clear communication between teams, and managing timelines and deliverables. Regular meetings, stakeholder updates, and agile project management practices are commonly used to keep everyone aligned and to adapt quickly to changing priorities. Building strong relationships across departments is essential for successfully delivering data-driven solutions.

Do program managers need data analytics skills?

Program managers in data analytics roles typically need skills in data analysis, visualization tools, and understanding of data-driven decision-making. These skills help them oversee projects that involve large datasets and ensure strategic goals are met efficiently.

What are the key skills and qualifications needed to thrive as a Program Manager in Data Analytics, and why are they important?

To thrive as a Program Manager in Data Analytics, you need strong project management skills, deep analytical expertise, and a background in statistics or computer science, often supported by a bachelor’s or master’s degree. Familiarity with analytics platforms (such as Tableau or Power BI), programming languages (like SQL or Python), and certifications like PMP or Agile are highly valuable. Exceptional communication, leadership, and stakeholder management skills help in aligning teams and translating complex data insights into actionable business strategies. These capabilities ensure successful delivery of analytics initiatives that drive informed decision-making and organizational growth.

What is a Program Manager in Data Analytics?

A Program Manager in Data Analytics is responsible for overseeing and coordinating multiple data analytics projects or initiatives within an organization. They work closely with data analysts, data scientists, and other stakeholders to ensure that data-driven projects align with business objectives, are delivered on time, and produce actionable insights. Their role includes strategic planning, resource allocation, risk management, and communication between technical teams and business leaders. Program Managers help bridge the gap between technical execution and organizational goals, ensuring that data analytics initiatives deliver measurable value.

Who earns more, a project manager or a data analyst?

A project manager typically earns more than a data analyst due to greater responsibilities, leadership requirements, and often higher levels of experience and certification. Project managers usually oversee entire projects, budgets, and teams, which contributes to higher compensation compared to data analysts who focus on data interpretation and reporting.
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Program Manager Data Analytics jobs near you
Director of Data & Analytics

Director of Data & Analytics

Barge Design Solutions, Inc.

Nashville, TN

Other

Posted 11 days ago

Job description

TheDirector of Data & Analytics leads Barge's Data & Analytics Center ofExcellence (COE) and builds the foundation for trusted, reusable data and selfserviceanalytics across the firm. This role is accountable for improving leadershipvisibility and decision speed by establishing shared enterprise measures,brokering definitions across business owners, and building a scalable dataplatform that enables better decisions and analytics.
Responsibilities:
Strategic Leadership:
  • Develop and execute the enterprise data strategy aligned to business priorities, digital modernization, and transformation initiatives
  • Create and maintain the enterprise data roadmap including data platforms, governance frameworks, data quality, and business intelligence initiatives
  • Foster a culture of enablement and partnership Data succeeds when business teams can move faster without dependency
  • Communicate clearly with both technical and nontechnical stakeholders ability simplify complex topics across personas
  • Build and lead a highperforming COE team; hire, coach, and develop talent while setting clear expectations and accountability
Data Governance & Quality:
  • Broker metric and data object definitions across Finance, Operations, Marketing, and HR to eliminate conflicting truths and reduce rework
  • Create reusable, wellgoverned datasets and semantic models that reduce manual blending and accelerate decisionmaking
  • Define federated data governance guardrails (quality, access, security, reuse) that enable business ownership while ensuring enterprise consistency
  • Partner with IT, Security and legal on data protection, risk management, regulatory compliance, and controls
  • Implement data quality monitoring, remediation processes, and continuous improvement mechanisms
Technology, Architecture & Analytics Enablement:
  • Build and evolve Barge's data platform to enable reliable reporting, scalable selfservice analytics, and future advanced analytics/AI
  • Partner closely with IT, Enterprise Applications, and Innovation to ensure data is integrated into core workflows and systems of record
  • Deliver and manage a small set of highvalue, crossenterprise reporting needs that are complex and businesscritical, while keeping most reporting selfservice
  • Establish measures of success for data and analytics adoption (usage, confidence, cycle time reduction) and communicate progress clearly
  • Improve leadership visibility and decision speed through trusted metrics and accessible analytics
  • Increase selfservice reporting adoption and reduce manual spreadsheet blending and reconciliation
  • Deliver a scalable data platform foundation that supports analytics and AI readiness

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