Top Remote Senior Level Data Management Jobs in Dallas, TX

Build reliable data models and semantic layer for AI-powered analyses. Support Product, Finance, and Customer Success with SQL-based analytics, BI dashboards, and stakeholder storytelling. Standardize data team processes, prioritize work, and collaborate across company to enable data-informed decisions.

The Data Scientist will analyze data to optimize products, drive business decisions, develop models and algorithms, and enhance customer experiences.

The Senior Data Engineer will build and maintain ETL/ELT pipelines, optimize SQL queries, and collaborate on machine learning workflows, driving data engineering best practices.

Design, build, and operate production-grade data ingestion pipelines and dbt transformations into a Databricks lakehouse. Establish data quality, monitoring, and observability. Partner with Product and Engineering to enable metrics, dashboards, and longitudinal patient analytics supporting clinical and operational decision-making.

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.