Senior Data Analyst, Enterprise Analytics

Insperity•Houston, TX

About The Position

The Senior Data Analyst is a strategic analytics partner within Enterprise Analytics, supporting high-priority initiatives across multiple business functions through data-driven decisions, trusted measurement, and actionable insights. The role translates complex business questions into analytical frameworks, measurable outcomes, and executive-ready recommendations, partnering with business leaders, platform owners, Data Engineering, Data Governance, and technology teams to establish trusted metrics and scalable analytics capabilities. The position initially focuses significantly on Marketing Analytics, Customer Data Platform (CDP) initiatives, customer insights, and related data platform efforts, while remaining a flexible resource for analytical needs across the enterprise. Within the Enterprise Data Foundation, the analyst helps establish consistent business definitions, governed metrics, analytical standards, and scalable reporting practices. The role calls for strong analytical and technical capabilities, a consultative mindset, substantial independent judgment, and the ability to translate business objectives into measurable outcomes and recommendations.

Requirements

Bachelor’s degree in Analytics, Business, Information Systems, Marketing, Data Science, Statistics, Computer Science, or a related discipline, or equivalent relevant experience.
Five or more years of experience in analytics, business intelligence, marketing analytics, consulting, data analysis, or related fields.
Experience supporting Marketing, Revenue Operations, Customer Experience, CRM, CDP, marketing automation, or similar business functions.
Experience translating business objectives into analytical requirements, measurement approaches, and actionable recommendations.
Experience working across business and technical teams in collaborative environments.
Strong business acumen and ability to translate organizational objectives into analytical solutions, measurable outcomes, and data-informed recommendations.
Strategic consulting skills, including assessing business needs, challenging assumptions, identifying opportunities, and guiding stakeholders toward effective solutions.
Advanced analytical and problem-solving skills, including SQL development, statistical analysis, hypothesis testing, root-cause analysis, KPI development, and performance measurement.
Critical thinking skills to evaluate complex issues, synthesize multiple information sources, and develop actionable recommendations.
Ability to translate complex data into business insights through data storytelling, visualization, and executive-level communication.
Stakeholder management skills, including building trusted partnerships, influencing decisions, and aligning priorities across diverse groups.
Strong understanding of marketing analytics, including customer segmentation, attribution methodologies, campaign measurement, lead lifecycle management, funnel analytics, customer engagement, and marketing operations.
Experience with business intelligence and reporting tools such as Tableau, CRM Analytics, Power BI, or similar visualization platforms.
Knowledge of dashboard design principles, visualization best practices, and user-focused reporting solutions.
Familiarity with cloud data environments, including Snowflake or comparable data warehouses, data modeling, ETL/ELT processes, semantic layers, metadata management, and data lineage concepts.
Knowledge of data governance, data quality management, data stewardship, governed metrics, and enterprise reporting standards.
Ability to collaborate across business, marketing, technology, analytics, and data engineering teams to deliver scalable analytical solutions.
Commitment to continuous improvement through process optimization, automation, innovation, and modern analytics practices.

Nice To Haves

Experience working with customer data platforms, marketing technology solutions, marketing automation platforms, or customer engagement technologies.
Experience supporting data governance, KPI management, and enterprise reporting practices.
Relevant certifications in analytics, business intelligence, Salesforce, cloud data platforms, marketing technology, or data governance.
Preferred experience with Python, including Pandas and NumPy; dbt or similar transformation frameworks; AI-assisted analytics tools; Salesforce; and marketing technology implementations.

Responsibilities

Translate business objectives into analytical frameworks, success measures, actionable insights, and data requirements.
Facilitate discovery and requirements-gathering sessions to identify underlying business needs.
Help stakeholders clarify objectives, KPIs, business definitions, dependencies, and success criteria; constructively challenge assumptions.
Lead ambiguous, cross-functional analytical engagements from problem framing through recommendation, aligning stakeholders on scope, decision criteria, tradeoffs, and outcomes.
Build trusted partnerships and influence business and technical stakeholders toward practical, data-informed decisions.
Convert complex analytical findings into clear business recommendations and executive-ready narratives.
Support the shift from reactive reporting to consultative, decision-focused analytics.
Develop analyses, dashboards, scorecards, and reporting solutions for marketing strategy, campaign effectiveness, funnel performance, attribution, customer engagement, and business growth.
Partner with Marketing, Sales, and Service leaders to maintain aligned metrics across functions.
Perform trend analysis, root-cause analysis, segmentation, forecasting, and KPI development.
Support executive reporting and communicate findings to drive adoption and action.
Identify opportunities to improve data literacy, measurement practices, and decision effectiveness across Marketing.
Work with the Marketing Platform Manager to support implementation, adoption, governance, and measurement of marketing technologies, including CDP, Salesforce, CRM Analytics, and Tableau.
Define, validate, and document audience logic, business rules, segmentation requirements, activation criteria, and performance measurement methodologies.
Translate platform use-case requirements into analytical specifications and measurement frameworks.
Evaluate platform effectiveness using adoption metrics, data-quality indicators, audience performance, and business outcomes.
Bridge Marketing, Analytics, Data Engineering, and Technology teams.
Promote trusted reporting through data governance, quality, documentation, transparency, and consistency.
Help develop and maintain common metric definitions, business glossaries, data lineage documentation, ownership models, and enterprise standards.
Help define and validate shared definitions for customers, leads, accounts, campaigns, audiences, and other enterprise marketing concepts.
Identify data-quality concerns and partner with technical teams to prioritize remediation.
Support Enterprise Data Foundation governance initiatives, data readiness, and analytical standards.
Develop and maintain advanced SQL queries, analytical datasets, and curated reporting assets.
Collaborate with Data Engineering on semantic layers, curated datasets, data models, and analytical requirements.
Support testing, validation, and quality assurance for analytical solutions.
Work with modern cloud data environments and enterprise-scale datasets to support analytical accuracy and scalability.
Use AI-assisted analytics, automation, and modern development practices where appropriate and consistent with enterprise standards.