BI Analytics Engineer

Saxon Global•Irving, TX

3d•Onsite

About The Position

The BI Analytics Engineer III will be responsible for designing, developing, and maintaining enterprise-grade BI and analytics solutions. This role involves building optimized semantic models, datasets, and dashboards, as well as developing and maintaining data models (star/snowflake schemas) for analytics and reporting. The engineer will write complex, high-performance SQL queries, optimize workloads, and design and implement predictive models (regression, classification, forecasting, clustering). Additionally, the role includes developing, training, evaluating, and deploying machine learning models in production environments, translating business requirements into analytics solutions and KPIs, and implementing feature engineering, model validation, and performance monitoring. Collaboration with data engineers, data scientists, and business stakeholders is essential, along with ensuring data accuracy, governance, and security across BI and analytics platforms. Automation of analytics workflows and reporting pipelines is also a key responsibility. Travel and/or relocation to various unanticipated locations throughout the U.S. may be required to work with clients on projects, with the frequency determined by client needs. The role utilizes SQL Server, SQL Server Integration Services, SQL Server Reporting, Crystal Reports, and UNIX.

Requirements

Master's Degree in Computer Applications, Computer Information Systems, Computer Science, Engineering, or related field.
Twelve (12) months of experience.
One (1) year of experience must have included: SQL Server, SQL Server Integration Services, SQL Server Reporting, Crystal Reports, UNIX.
Travel and/or Relocation to various unanticipated locations throughout the U.S. required.

Responsibilities

Design, develop, and maintain enterprise-grade BI and analytics solutions.
Build optimized semantic models, datasets, and dashboards.
Develop and maintain data models (star/snowflake schemas) for analytics and reporting.
Write complex, high-performance SQL queries and optimize workloads.
Design and implement predictive models (regression, classification, forecasting, clustering).
Develop, train, evaluate, and deploy machine learning models in production environments.
Translate business requirements into analytics solutions and KPIs.
Implement feature engineering, model validation, and performance monitoring.
Collaborate with data engineers, data scientists, and business stakeholders.
Ensure data accuracy, governance, and security across BI and analytics platforms.
Automate analytics workflows and reporting pipelines.