Analytics Engineer: Data Pipelines & Dashboards

Jockey International, Inc.; Kenosha (WI); On-site; USD 75,000 - 110,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

401(k)

Educational support

Volunteer program

Employee discounts

Wellness programs

Career growth

Job summary

Jockey International, Inc. in Wisconsin seeks an Associate Analytics Engineer to deliver clean data sets and empower end users with insights.

You will transform, test, deploy, and document data in the data lake, applying version control and CI practices while collaborating with business users, analysts, and engineers. You will build data pipelines in SQL and Python, develop dashboards with Tableau, Sigma, or Power BI, and help expand our data warehouse for ML and analytics.

Qualifications

• Internship, academic project, or professional analytics experience.
• Working knowledge of SQL and querying data.
• Experience building dashboards with Tableau, Sigma, or Power BI.
• Strong analytical skills and problem solving.
• Attention to detail and data accuracy.
• Ability to learn quickly and manage priorities in a fast-paced environment.

Responsibilities

• Develop data pipelines in SQL and Python to deliver data to end users.
• Build and maintain dashboards and reports on Tableau/Sigma/Power BI.
• Collaborate with data scientists, ML engineers, analysts, and business users.
• Ensure data quality, integrity, and consistency across environments.
• Expand the data warehouse with clean data for analysis.
• Translate business requirements into technical specs; support data architecture improvements.
• Other duties as assigned.

Skills

SQL

Data analysis

Dashboarding

Python

Attention to detail

Education

Bachelor's degree in Data Analytics or related field

Tools

Tableau

Sigma

Power BI

dbt

Databricks

Snowflake

Job description

Jockey International, Inc. in Wisconsin seeks an Associate Analytics Engineer to deliver clean data sets and empower end users with insights.

You will transform, test, deploy, and document data in the data lake, applying version control and CI practices while collaborating with business users, analysts, and engineers. You will build data pipelines in SQL and Python, develop dashboards with Tableau, Sigma, or Power BI, and help expand our data warehouse for ML and analytics.