1

Senior Manager Data Analytics Jobs in Raleigh, NC

next page

Showing results 1-20

Senior Manager Data Analytics information

See Raleigh, NC salary details

$43.7K

$111.3K

$163.8K

How much do senior manager data analytics jobs pay per year?

As of Jun 17, 2026, the average yearly pay for senior manager data analytics in Raleigh, NC is $111,276.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,900.00 and $131,200.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Manager Data Analytics, you need advanced expertise in data analysis, statistical modeling, and business intelligence, typically supported by a degree in a quantitative field and several years of analytics experience. Proficiency with analytics tools such as SQL, Python, R, and platforms like Tableau or Power BI, as well as experience with data warehousing systems, is essential. Strong leadership, strategic thinking, and communication skills enable you to guide teams and translate complex findings into actionable business insights. These competencies are crucial for driving data-informed decision-making and maximizing organizational value from analytics initiatives.

What does a Senior Manager Data Analytics do?

A Senior Manager Data Analytics leads teams that analyze large sets of data to help organizations make informed business decisions. They develop analytics strategies, oversee data projects, and ensure the quality and integrity of data-driven insights. This role often involves collaborating with other departments, mentoring analysts, and presenting key findings to senior leadership. Senior Managers in this field need strong technical skills, leadership abilities, and business acumen to drive impactful results.

How does a Senior Manager of Data Analytics typically collaborate with cross-functional teams within an organization?

Senior Managers of Data Analytics frequently work alongside cross-functional teams such as IT, product development, marketing, and finance to ensure that data-driven insights align with business objectives. They are responsible for translating complex analytical findings into actionable recommendations and communicating these insights clearly to both technical and non-technical stakeholders. Regular collaboration often involves leading meetings, setting project priorities, and ensuring data initiatives are integrated smoothly with ongoing business strategies. This collaborative environment fosters innovation and helps drive organizational growth.

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

AspectSenior Manager Data AnalyticsData Analyst
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related field; extensive experienceBachelor's degree in related field; entry to mid-level experience
Work EnvironmentLeadership roles, strategic planning, team managementData collection, analysis, reporting
Employer & Industry UsageCorporate, finance, healthcare, tech companiesVarious industries, including marketing, finance, tech
Common Search & ComparisonOften compared for leadership and strategic rolesCompared for technical and analytical skills

The main difference between Senior Manager Data Analytics and Data Analyst lies in their responsibilities and experience level. Senior Managers focus on strategic oversight, team leadership, and decision-making, while Data Analysts handle data collection, analysis, and reporting at a more technical level. Senior Managers typically have more experience and credentials, working in leadership roles within organizations across various industries.

What are popular job titles related to Senior Manager Data Analytics jobs in Raleigh, NC? For Senior Manager Data Analytics jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Senior Manager Data Analytics jobs in Raleigh, NC look for? The top searched job categories for Senior Manager Data Analytics jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Senior Manager Data Analytics jobs? Cities near Raleigh, NC with the most Senior Manager Data Analytics job openings:
Infographic showing various Senior Manager Data Analytics job openings in Raleigh, NC as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $111,276 per year, or $53.5 per hour.
Senior Manager, Data, Analytics & AI

Senior Manager, Data, Analytics & AI

ACA Group

Durham, NC

Other

Posted 3 days ago


Job description

Senior Manager, Data Analytics and AI - Global Regulatory Advisory will build and scale the data infrastructure, analytics, and AI-enabled automation that power how ACA's Global Regulatory Advisory business operates. Partnering closely with the Head of Operations, Global Regulatory Advisory, and business, finance, and technology leaders across multiple advisory segments, this role will unify fragmented operational, project, client, and financial data into a reliable single source of truth. The role will also deliver executive-ready reporting on utilization, profitability, bookings-to-revenue conversion, and other core KPIs. Success is defined by measurable improvements in data quality, reporting speed and consistency, and the adoption of repeatable, data-led operating rhythms that increase efficiency, margin, and client delivery excellence.

The Opportunity:

ACA Group is building the operational backbone for its next phase of growth-and this role is at the center of it. - Strategy & Operations, you will partner directly with the Head of Operations for ACA's Global Regulatory Advisory business to architect, build, and scale the data infrastructure and analytics capabilities that power how we run, measure, and grow a multi-segment, ~$100M+ advisory practice.

Today, our US Regulatory business spans Private Funds, Fund Officers, Broker Dealer, and Wealth-each with its own delivery model, client base, and operational rhythm. Your mandate is to build and maintain a data and analytics backbone that helps operationalize and systematize how we analyze disparate data at scale, maximize business efficiency and profitability, and create a unified data schema that empowers both practice-level insight and enterprise-level clarity-while maintaining an exceptional client experience for our delivery teams.

You will own the design and implementation of scalable data systems, AI-driven automation, and advanced analytics that enable leadership to manage the business through a single, data-led operating lens-from utilization and scorecard tracking to project profitability, revenue recognition, and management reporting. This is not a support role. This is a builder's role-high autonomy, high impact, and a direct line to the decisions that shape how ACA's largest advisory business operates and scales.

If you're energized by the idea of turning messy, real-world operational data into clean, automated, decision-grade intelligence-and you want to do it inside a fast-moving, PE-backed GRC leader-this is your opportunity.

Job Duties:

  1. Design and build scalable data architecture to unify fragmented product, project, billing, and client engagement data across multiple business segments and legacy systems (PSA tools, CRM, Deltek, Power BI, finance platforms, Workday, manual spreadsheets).

  2. Develop and deploy AI and automation solutions to reduce manual rework in operational workflows, including capacity and utilization reporting, project profitability analysis, data aggregation, cross-functional data migrations, and client engagement hygiene tracking.

  3. Build and maintain advanced dashboards and analytics tools using Power BI, Python, and Excel to deliver real-time, decision-grade visibility into key operational KPIs such as billable utilization, project profitability, cost-to-serve drivers, bookings-to-revenue conversion, and termination/churn analytics.

  4. Integrate disparate data sources across the enterprise (Salesforce, PSA/project management tools, Power BI, SharePoint, finance systems) via APIs and automated ETL pipelines to establish a reliable single source of truth for operational reporting.

  5. Partner cross-functionally with Business Unit Leaders (Private Funds, Fund Officers, Broker Dealer, Wealth), FP&A, Human Resources, and Technology to ensure data definitions, reporting cadences, and KPI frameworks are standardized and aligned to the firm's financial and operational rhythms.

  6. Support the development and automation of management reporting cycles, including quarterly business reviews, monthly financial reviews, and board-level materials-transforming manual, labor-intensive reporting into repeatable, data-driven operating systems.

  7. Quantify operational constraints and opportunities through rigorous analysis-identifying where execution mechanics (data classification errors, billing discrepancies, non-billable capacity inefficiencies) are creating drag on margin and growth, and recommending data-backed improvements.

  8. Prototype and scale AI agents and tools (e.g., Copilot-based automation, custom Python scripts, LLM-assisted workflows) to accelerate reporting, analysis, and decision-making across the US Regulatory team.

  9. Champion a data-led culture within the operations function by establishing SOPs for data governance, reporting standards, and analytics best practices that can be replicated across ACA's global advisory businesses.

Required Education and Experience:

  • Bachelor's degree, preferably in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, Finance, or a related discipline.
  • At least 7-10 years of progressive experience in data analytics, quantitative analysis, business intelligence, or quantitative software/application development, ideally within professional services, financial services, or an advisory environment.
  • Advanced proficiency in Python for data manipulation, automation, and analysis (pandas, NumPy, scripting, API integrations).
  • Proven expertise leveraging AI tools (e.g., Copilot, Claude) in an enterprise environment to drive scalable efficiencies (automation, agent-building, workflow optimization, reporting, QC analysis).
  • Expert-level skills in Microsoft Excel (complex modeling, Power Query, VBA/macros) and Power BI (DAX, data modeling, dashboard design, publishing).
  • Demonstrated experience building APIs and automated data pipelines/ETL processes across enterprise systems.
  • Proven ability to work with large, complex, disparate datasets-cleaning, reconciling, and structuring data into reliable analytical outputs.
  • Experience partnering cross-functionally with senior business leaders, finance teams, and technology stakeholders to translate operational needs into analytical solutions.

Preferred Education and Experience:

  • Experience in a high-growth, private equity-backed, or professional services environment.
  • Familiarity with GRC (governance, risk, and compliance), regulatory advisory, or financial services operations.
  • Hands-on experience with AI/ML tools, large language models, or AI agent development (e.g., Microsoft Copilot, OpenAI APIs, Claude).
  • Experience with Salesforce reporting, PSA/project management platforms, and financial planning tools.
  • Master's degree in a quantitative discipline, MBA, or equivalent advanced training.
  • Prior experience building or scaling a data/analytics function within a complex organization.

Required Skills and Attributes:

  • Builder's mindset: thrives in ambiguity and creates structured, scalable solutions from scratch.
  • Strong operational intuition: connects data to business decisions and understands impact on outcomes.
  • High ownership: takes initiative and drives work from concept through delivery.
  • Cross-functional fluency: effectively translates between business, finance, and technical stakeholders.
  • Precision and rigor: prioritizes data quality, consistency, and analytical integrity.
  • Intellectual curiosity: stays current on emerging tools, especially in AI, automation, and data engineering.
  • Excellent communication skills: able to present complex insights in clear, executive-ready formats.