Top Hybrid Data & Analytics Jobs in Dallas-Fort Worth, TX

Lead data architecture strategies, drive innovation in data solutions, and oversee compliance with governance and security policies while collaborating with stakeholders to align technical solutions with business needs.

As a Principal Data Analyst, you'll innovate, build and maintain data solutions using scripting languages and cloud services to tackle business problems, providing insights and managing data quality.

The Senior Data Engineer designs and builds ETL/ELT data pipelines, collaborates with teams for data solutions, and optimizes data processes.

The Director, Quantitative Risk Management leads model development for financial products, oversees new product analysis, and ensures model compliance and performance monitoring while managing a team of engineers.

The role focuses on developing data-driven strategies to identify risks and support growth in a banking context, involving complex analytics and stakeholder engagement.

Designs data models, creates reusable schemas, maintains data dictionaries, and translates business requirements into technical specifications to enhance data governance.

Lead the data strategy and oversee project execution for data management, integration, and governance while collaborating with stakeholders and cross-functional teams.

The Senior Data Engineer will architect and implement data pipelines, manage their performance, and partner with stakeholders to ensure data accessibility and quality. Responsibilities include assessing data sourcing needs and providing visibility into pipeline status.

The Sr. Manager, Monitoring and Analytics will execute monitoring controls, develop analytics frameworks, and collaborate with various teams to ensure accurate reporting and issue resolution.

The Enterprise Data Architect will define and govern enterprise data architecture, ensuring data quality and discoverability, while leading cross-functional teams to innovate and implement scalable data management solutions.

The role requires leadership in enterprise data management, focusing on MDM, governance, data quality, and architecture, ensuring high-quality, trusted data for analytics and operational use, while managing a team and collaborating with stakeholders.