Top Senior Level Data & Analytics Jobs in Salt Lake City, UT

The Senior Data Scientist will lead data analysis and machine learning efforts to extract insights from complex datasets, drive product enhancements, and influence strategic decision-making. Responsibilities include statistical modeling, data mastery, and mentorship within a cross-functional team to deliver machine learning solutions.

The Senior Data Engineer will develop a cloud-based data transformation and workflow solution for the U.S. Army. Responsibilities include managing data pipelines, data security governance, and delivering high-quality software. The role entails communicating design decisions to different audiences and requires extensive collaboration across teams to solve complex problems.

This role involves leading a team of Data and Software Engineers responsible for ingesting and processing critical loan data from multiple partners. The manager will mentor and train team members, participate in code reviews, manage large-scale projects, and collaborate with project management to improve engineering processes.

As a Lead Data Engineer, you will design, develop, and implement data pipelines, warehouses, and lakes while ensuring data quality and accuracy. You will lead strategic discussions, document requirements, and develop scalable data solutions. Additionally, you will maintain data infrastructure and stay updated on emerging technologies.

The Operations & Analytics Manager at Aptos will develop strategic plans to optimize operations, manage resources, enhance ecosystem growth, conduct data analytics, and mitigate risks. This role involves collaborating closely with leadership and various departments within the organization.

The GCP Data Engineer will design, build, and maintain large-scale data infrastructure, optimizing data processing, ensuring data quality, and collaborating with cross-functional teams to implement scalable solutions for analytics and business intelligence.

The Principal Data Engineer will design, develop, and maintain ETL pipelines for data acquisition and transformation. Responsibilities include collaborating with teams to understand data needs, utilizing AWS Glue, optimizing ETL processes, and applying data governance practices. The role requires strong technical skills in Python, Spark, and SQL, along with experience in data matching and analytics.