Top Senior Data & Analytics Jobs in Dallas, TX

Performs independent quality assurance and validation across enterprise data platforms, warehouses, integrations, reporting solutions, and business processes. Responsibilities include data quality analysis, test strategy and automation, regression and release validation, incident investigation, root cause analysis, requirements traceability, governance, regulatory validation, and monitoring data quality metrics. The role partners with engineering, business, compliance, and operational teams while improving enterprise data integrity, reliability, and governance.

Administer and sustain InterSystems IRIS and Caché database environments supporting VA healthcare data migration and EHR modernization. Responsibilities include configuration, upgrades, troubleshooting, replication, performance tuning, capacity planning, backup and recovery, high availability, monitoring, documentation, and production support across development through production environments. The role requires Linux administration, cross-functional collaboration, on-call support, U.S. citizenship, and eligibility for a Government Public Trust clearance.

Lead production support and continuous improvement for an Azure and Databricks data platform. Responsibilities include incident resolution, root-cause analysis, stakeholder communication, monitoring, performance and cost optimization, data quality and governance, change and release management, KPI reporting, documentation, training, and automation including self-healing capabilities.

Operationalize data governance policies and standards across technology and business domains. Maintain metadata repositories and data catalogs, manage data quality exceptions, coordinate remediation, monitor governance metrics, and build Power BI dashboards. Partner with data stewards, owners, project managers, Scrum Masters, and agile delivery teams to embed governance requirements, manage risk, improve data quality, and increase adoption. Provide guidance, documentation, education, and reporting in a regulated enterprise environment.

Leads item management operations, including item creation, maintenance, mapping, taxonomy governance, data quality resolution, and reporting. Coordinates internal stakeholders and external partners to standardize product information and identifiers across systems. Oversees project cadence, issue resolution, corrective actions, team workload, coaching, and performance management. Supports data governance, taxonomy standards, and system implementation initiatives.

Oversee enterprise finance platforms and data workflows, including data-flow architecture, integration mapping, master data governance, data quality standards, platform documentation, and automated workflows. Monitor integration health, resolve data anomalies, and partner with finance, IT, and business leaders on platform initiatives. Requires strong SQL, relational database, data modeling, governance, analytical, communication, and project coordination skills.

Own digital analytics, reporting, dashboard development, data extraction, ETL, and AI-enhanced insight generation for luxury e-commerce. Partner with business leaders and online retail teams to translate questions into analysis, identify trends and opportunities, improve KPIs, and create self-service reporting. Present clear recommendations to leadership, maintain data governance, validate AI-generated insights, and support data and AI initiatives.

Lead the enterprise Data Quality (DQ) Issue Management program end-to-end: establish and enhance issue management framework, drive identification, classification, root-cause analysis, remediation tracking, and closure validation. Partner with Divisional Data Offices, Technology FDO, and Non-Financial Risk to enforce standards, ownership, and escalation. Define KPIs/KRIs, assess controls, deliver reporting and training, and embed sustainable practices across data lineage, control frameworks, and remediation plans to reduce systemic DQ risk.

Leads pricing analytics and develops data-driven pricing strategies to optimize gross profit, competitiveness, and customer acceptance. Builds reporting and dashboards, advises network and merchandising teams, supports AI-powered pricing solutions, digitizes processes, and drives experimentation and continuous optimization. Collaborates with Data, Sales, Transformation, Purchasing, and Category Management teams to translate business requirements into pricing solutions and communicate recommendations across the branch network.

Leads the Underwriting Data Engineering team and oversees the design, development, and productionization of scalable data and machine learning pipelines. Responsibilities include feature engineering, data preparation, model deployment, data validation, governance, monitoring, API integration, analytic data products, roadmap development, stakeholder collaboration, and team coaching.