Analytics Engineer III

QTS Data Centers•Overland Park, KS

About The Position

The Analytics Engineer III role is responsible for bridging the gap between, data miners, product managers, and other Data Science & Engineering teams, and mentoring junior members of the analytics engineering team in designing analytics solutions in Snowflake. You’ll be providing expertise in data modeling and data warehousing concepts, and leveraging modern data stack technologies, including Snowflake and dbt, to drive actionable insights. Your experience in improving data quality will help the business gain trust in the data. RESPONSIBILITIES, other duties may be assigned. Monitoring, maintaining, and improving data integration logic running in the Snowflake Data Cloud. Design, implement, and optimize large-scale data analytics solutions based on the Snowflake Data Warehouse, leveraging data to drive significant business impact. Utilize dbt to create data pipelines, manage transformations, and orchestrate data workflows. Providing expertise in data warehousing concepts, data modeling, and data lake architecture Use SQL, Tableau, Python, or any combination of tools to develop rapid prototypes and educate stakeholders on analytics modeling. Provide expert advice and education in the usage and interpretation of data to other teams across Data Science, Data Engineering, and functional Business Units. Detecting data quality issues and their root causes. Evolving the way data is organized and maintained.

Requirements

Bachelor's or Master's degree in Business Analytics, Computer Science, Mathematics, or related fields; or equivalent experience.
5+ years experience using SQL
2+ years of experience using dbt and Snowflake Data Cloud
2+ years of experience working within a CICD framework.
Advanced understanding of data warehousing concepts and modern data stack tools, specifically dbt and Snowflake Data Cloud
Working knowledge of SCRUM and Kanban Agile methodologies
Effective communication of technical findings to non-technical stakeholders is imperative.
Ability to translate data insights into actionable business recommendations.
Analytical mindset to tackle complex data challenges.
Adaptability to changing requirements and priorities.
Ensuring data accuracy and quality.
Staying updated with industry trends and emerging technologies.
Ability and willingness to mentor less experienced team-members

Responsibilities

Monitoring, maintaining, and improving data integration logic running in the Snowflake Data Cloud.
Design, implement, and optimize large-scale data analytics solutions based on the Snowflake Data Warehouse, leveraging data to drive significant business impact.
Utilize dbt to create data pipelines, manage transformations, and orchestrate data workflows.
Providing expertise in data warehousing concepts, data modeling, and data lake architecture.
Use SQL, Tableau, Python, or any combination of tools to develop rapid prototypes and educate stakeholders on analytics modeling.
Provide expert advice and education in the usage and interpretation of data to other teams across Data Science, Data Engineering, and functional Business Units.
Detecting data quality issues and their root causes.
Evolving the way data is organized and maintained.