Top Senior Data & Analytics Jobs in Greensboro, NC

Conducts operations research and advanced analytics to optimize public-sector command performance and reduce costs. Develops optimization, statistical, simulation, regression, mathematical, and decision-analysis models; implements analytical models in Python; performs data analysis; supports software development; assesses operational questions; and prepares decision briefings, reports, presentations, and recommendations for senior leadership.

Lead the design and operation of a scalable data platform, owning ingestion, orchestration, observability, lineage, data modeling, contracts, and ETL/ELT pipelines. Build Databricks and PostgreSQL solutions, implement data-quality controls, anomaly detection, governance, privacy, and compliance practices, and establish reusable engineering standards. Mentor engineers and ensure reliable, traceable data across markets and product lines.

Own and evolve Worldly’s production data lake, Postgres warehouse, CDC and streaming pipelines, dbt transformations, orchestration, BI access controls, and graph integrations. Maintain reliable, governed analytics infrastructure using Iceberg, Trino, Dagster, Terraform, and AWS. Support production generative AI workflows involving embeddings, similarity search, extraction, and classification. Responsibilities include data quality, monitoring, security, incident response, disaster recovery, schema governance, and collaboration with data science and analytics stakeholders.

Develops and automates complex sales reports and dashboards using Power BI, SQL, SSRS, SSIS, Excel, and related tools. Performs data transformation, cleansing, modeling, analysis, reconciliation, and integrity controls. Serves as a reporting subject matter expert, supports partners and leadership, resolves reporting escalations, mentors analysts, and contributes analytics to revenue-growth initiatives.

Architect and maintain NetBrain’s first cloud data warehouse, ELT pipelines, transformation layer, semantic models, and BI foundation. Own data quality, governance, lineage, access controls, and curated models supporting product usage, customer adoption, account health, and go-to-market reporting. Partner with stakeholders to establish reliable metrics and a standardized source of truth, while supporting AI-assisted analytics and natural-language reporting use cases.

Build business intelligence solutions, dashboards, data models, market-sizing forecasts, and executive reporting for Cisco’s Market Insights team. Analyze large internal and external datasets to identify trends, opportunities, and risks. Apply LLMs and agentic workflows to synthesize unstructured information and automate reporting. Partner with Sales, Product Management, and Strategy to translate business questions into actionable insights and recommendations.

Leads enterprise data strategy, platform architecture, Master Data Management, federated governance, data quality, compliance, and real-time analytics. Builds scalable data infrastructure, modernizes legacy pipelines, establishes operational data hubs, and enables secure data products across the enterprise. Oversees data engineering, architecture, MDM, governance, and embedded analytics teams while partnering with executives and business units to drive transformation, operational efficiency, AI readiness, and acquisition integration.

Build and maintain data models, pipelines, metrics, dashboards, and analytics supporting identity graph construction, entity matching, and identity resolution. Partner with engineering and data science teams to productionize matching logic, evaluate match quality, monitor data quality and drift, and manage identity-provider relationships. Translate complex identity concepts into actionable insights for technical and non-technical stakeholders while helping define privacy-conscious product and data priorities.

Design and lead scalable, secure, highly available database infrastructure for multi-terabyte SQL Server environments. Set technical direction for data architecture, performance, real-time pipelines, security, and growth. Troubleshoot complex production issues, optimize queries and indexes, guide cross-functional projects, mentor engineers, review changes, reduce technical debt, and evaluate emerging technologies. Monitor database health using Splunk, Datadog, and Grafana while influencing engineering and Site Reliability strategy.

Design, build, and own scalable data pipelines and warehousing architecture from ingestion through analytics and incentive payouts. Lead data platform architecture, dbt modeling, data quality, lineage, observability, performance, and cost management. Partner with engineers and analysts on telematics accuracy and driver incentive reporting. Use AI coding tools daily to develop and review pipelines, SQL, and data models.