Top Remote Senior Level Data Management Jobs in Dallas, TX

Lead AI enablement and reporting for Workday HCM by defining strategy, designing scalable reporting and automation, partnering with HR stakeholders, building Custom Reports, Discovery Boards, and Prism Analytics, and evaluating emerging AI tools to improve HR operations and data-driven decision-making.

Serve as primary DBA SME bridging on-premises SQL Server to Microsoft Fabric. Design hybrid database architectures, implement cloud-based SQL services, establish Data Operations processes and SLAs, manage data integration, security controls, performance tuning, monitoring, and disaster recovery to support analytics and AI workloads.

Design and maintain company-wide dashboards, define KPI frameworks, implement tracking and data governance, write advanced SQL, partner with product and engineering, build predictive/AI-ready data layers, automate reporting, and present insights to leadership to drive operational and financial improvements.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

The Senior Data Engineer will design, build, and support data environments, orchestrate pipelines, and implement data solutions for advanced analytics and machine learning, working closely with project teams.

Lead design and delivery of scalable data architectures, pipelines, and trusted datasets. Drive data governance, cloud-native solutions, ETL/ELT, API integrations, and mentor engineers while ensuring reliability, security, and performance across analytics platforms and customer-facing data services.

The VP Global Grid Modeling will lead global data strategy, manage high-performing teams, ensure quality datasets, and engage with customers for insights in energy markets.