Analytics Engineer

Livestock Nutrition Center•Overland Park, KS

3d•Onsite

About The Position

The Analytics Engineer designs, builds, and maintains data pipelines and models while also delivering stakeholder-facing dashboards and analysis, bridging the gap between raw data infrastructure and business decision-making. This role requires 2-5 years of relevant experience and reports into the Technology department. At this time, this position is not eligible for employer-sponsored visa sponsorship or related sponsorship funding.

Requirements

Bachelor's degree in Data Science, Computer Science, Information Systems, or a related field, or equivalent practical experience.
2-5 years of experience in analytics engineering, data engineering, or a related analytics role.
Hands-on experience with data ingestion and preparation tooling, dbt for data modeling, and Tableau for dashboarding and visualization.
Strong SQL skills and hands-on experience with Snowflake as the primary data warehouse platform, along with a working understanding of on-premises data technologies and how they integrate within a broader data pipeline.
Familiarity with version control systems such as Git and standard development tooling.
Proficiency with standard office productivity tools such as Excel and Outlook.
Strong communication skills with the ability to translate technical data concepts for non-technical stakeholders.

Nice To Haves

Experience leading or managing projects, particularly within a data or analytics context, is a plus.
Priority consideration for experience in agricultural, livestock, or manufacturing industries.

Responsibilities

Support data ingestion and preparation processes to bring source data into the data warehouse, ensuring it is ready for downstream modeling.
Design, build, and maintain data transformation pipelines using dbt to model raw data into clean, reliable, and well-documented datasets.
Develop and maintain dashboards and visualizations in Tableau to support self-service reporting and stakeholder decision-making.
Perform ad hoc reporting and analysis to answer time-sensitive business questions outside of standard dashboard cycles.
Partner with business stakeholders to gather requirements, translate questions into data models, and deliver actionable insights, drawing on forecasting and analysis methods to proactively surface reporting opportunities.
Follow the company's change management process for data pipeline and dashboard changes, as defined by the Senior Integration and Systems Engineer.
Ensure data quality, consistency, and documentation across pipelines and models, including testing and validation within dbt, and maintain user-facing documentation to support stakeholder self-service.
Monitor and troubleshoot pipeline failures or data discrepancies and resolve them in a timely manner.
Collaborate with other technology and business teams to understand upstream data sources and downstream reporting needs, while building trust and driving adoption of BI tools and reporting standards across the organization.
Partner with internal technology resources, including development teams, to align data models with upstream system changes and support broader technology initiatives.
Lead small to mid-sized Salesforce or integration projects, such as new automation builds or point-to-point integrations, including planning, timelines, and stakeholder communication.
Identify opportunities to improve data infrastructure, modeling standards, and reporting efficiency over time.
Keeping assigned project work current on the technology project portfolio board, including status updates and timeline changes.