Top Senior Level Data Engineer Jobs in Las Vegas, NV

As an Analytics Engineer, you will create and optimize data models, work with product and engineering teams to ensure accurate data generation, collaborate with stakeholders on project timelines, and improve data processes using various analytics tools.

As a Principal Data Engineer, you will lead data engineering initiatives, architect integrated data platforms, maintain ETL pipelines, and utilize AWS services. Collaborating with various teams, you will ensure data efficiency and regulatory compliance while mentoring fellow engineers and optimizing data processes using advanced statistical methods and technologies like Docker, Snowflake, and Spark.

Sr. Analytics Engineer role at Paytient, partnering with various stakeholders to deliver data products driving operational efficiency and product improvement. Responsible for full-stack analytics engineering, data governance, creating actionable insights, and utilizing Machine Learning. Remote position in the continental U.S., excluding Montana.

The Senior Data Engineer will be responsible for designing and developing a robust data ingestion platform utilizing Azure technologies. Duties include creating complex data pipelines, writing SQL queries, ensuring data quality, and collaborating with teams for data modeling and analysis while adhering to compliance policies and practices.

The VP of Data and Content Engineering will lead data strategy and content initiatives, develop data models, enhance user experiences, promote engineering excellence, and collaborate with cross-functional teams to drive customer value and innovation for Flexera's platforms.

The Senior Data Engineer will develop robust and scalable data pipelines, architect innovative data products, and integrate advanced AI techniques to convert raw data into actionable insights, collaborating with various teams to enhance user experience.

The Senior Data Engineer will develop and maintain ETL/ELT pipelines, analyze and model complex data, and collaborate across teams to optimize data solutions for performance and scalability. Responsibilities include working with technologies like SQL, Python, and AWS, and ensuring data privacy and security in architectures.