Top Senior Level Data Engineer Jobs in Dallas, TX

As a Senior Data Engineer at Bluesight, you will design and maintain robust data architectures, facilitate effective data stewardship, and develop customer-facing data products. You'll work closely with engineering teams, product owners, and external clients to create and enhance data pipelines and governance practices, ensuring optimal purchasing decisions for hospital buyers.

The Staff Machine Learning Engineer will develop and fine-tune machine learning models, apply statistical techniques to analyze unstructured data, utilize pre-trained language models, optimize models for production, monitor performance, and work with teams to enhance product features and solutions.

The Senior Sales Business Intelligence Analyst will be responsible for designing, developing, and maintaining BI solutions to enable effective decision-making. This involves collaborating with stakeholders to understand reporting needs, creating user-friendly dashboards, and driving initiatives to improve reporting tools. The role requires strategic thinking and problem-solving skills, and an ability to communicate insights to senior management.

As a Senior Analytics Engineer, you will support decision-making by creating data models, improving telemetry collection, and building data quality tests. You will work closely with subject matter experts and lead the development of analytical tools in a cross-functional team environment.

The AI Data Leader will develop and implement an AI and data strategy, oversee innovation in AI technologies, collaborate with teams to implement solutions, build a high-performing team, drive data management and governance, supervise AI development, and ensure compliance with regulations.

The IT Data Analytics and Reporting Architect is responsible for designing data solutions that meet business requirements, focusing on BI Data Analytics tools like Snowflake, Matillion, and ETL processes. Responsibilities include overseeing project implementation, providing best practices knowledge, mentoring team members, and configuring ETL integration processes.

The role involves architecting, building, and maintaining reliable data pipelines, developing data applications in Python and SQL, ensuring data quality, and optimizing software engineering techniques while collaborating with IT and business teams.