Top Data & Analytics Jobs in Raleigh, NC

Owns go-to-market funnel reporting and analytics from lead generation through pipeline, bookings, and ARR. The role analyzes conversion, pipeline quality, CAC, LTV, marketing ROI, and sales efficiency across segments and channels. It builds dashboards, forecasts, and executive insights while partnering with Marketing, Sales, Revenue Operations, and Finance on attribution, data integrity, budgeting, and investment decisions.

Leads BI and analytics development by designing, optimizing, and governing dashboards, analytical models, semantic layers, SQL queries, and stored procedures across Cognos, QlikView, and Power BI. Collaborates with business, data science, visualization, and engineering teams to prepare data, develop machine learning or exploratory analytics solutions, automate production workflows, and deliver actionable insights. Provides technical leadership, mentors team members, establishes standards, reviews work, and promotes reusable components and best practices.

Design and implement data ingestion patterns, scalable data-sharing solutions, and automated Azure data pipelines for migrating a legacy warehouse to a Databricks lakehouse. Use Azure Data Factory, dbt, Medallion Architecture, Java, Python, and AI-assisted development tools while collaborating across teams to ensure secure, scalable, high-performing solutions.

Monitor and verify live sports data feeds during games, identify and resolve discrepancies in real time, cross-check multiple data sources, and escalate data issues. Maintain knowledge of game schedules, rosters, rule changes, and performance metrics to ensure accurate data interpretation. The role requires strong sports knowledge, exceptional attention to detail, focus during live events, and familiarity with spreadsheets, data tools, APIs, and real-time tracking systems.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

The Senior Data Engineer will transform real-world data into analytics-ready datasets, build scalable pipelines, and conduct analyses to support scientific and business decisions, collaborating closely with data science teams.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

Designs, executes, and analyzes AI-powered qualitative and quantitative opinion research. The role manages survey methodology, sampling, fieldwork, analysis, synthesis, reporting, client presentations, project budgets, and timelines. It also pilots AI applications, collaborates on intelligence platforms, translates data into strategic narratives, mentors junior staff, and supports proposals and business development.

Leads the Diagnostics business analytics strategy, roadmap, governance, and end-to-end delivery of dashboards, reporting, visualization, and AI-enabled solutions. Partners with executives and technology teams to define KPIs, drive adoption, measure value, and improve business outcomes. Builds and manages analytics, BI, business analysis, and product teams; oversees budgets, vendors, portfolios, resource planning, and organizational data literacy.

Build automated reports, dashboards, analytical workflows, benchmarks, and machine-learning solutions using utility and AMI data. Analyze outages, power quality, reliability, and device performance to identify trends and improvement opportunities. Support customer onboarding, reporting configuration, data validation, and operational analytics while partnering with Product, Engineering, Analytics, and NOC teams.