Hybrid BI & Data Analytics Intern

Wellness Pet LLC

United States

Hybrid

USD 40,000 - 57,000

Full time

11 days ago

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Job summary

The Wellness Pet Company is seeking a data analytics intern to support the development and enhancement of BI dashboards and data models. You will write SQL queries, assist with data cleansing and ETL processes, and analyze sales and operational data to translate findings into actionable insights.

You will collaborate with cross-functional teams, gain exposure to data governance and modern analytics tools like Power BI, Python, and Snowflake, and contribute to data-driven decision making while

Qualifications

  • Pursuing a bachelor's degree in a related field (Analytics, CS, IS, Statistics, Math, Finance).
  • Strong interest in using data to solve business problems and support decision making.
  • Familiarity with data visualization tools and SQL is preferred.

Responsibilities

  • Develop BI dashboards and data models for cross-functional teams.
  • Write and optimize SQL queries to extract and validate data from multiple sources.
  • Assist with data cleansing, validation and ETL/ELT processes to ensure accurate reporting.
  • Analyze sales and operations data to identify trends and opportunities for improvement.
  • Collaborate with stakeholders to deliver data-driven reporting and analytics solutions.
  • Support ad hoc reporting and BI projects, presenting findings clearly.

Skills

SQL
Analytical thinking
Communication

Education

Pursuing bachelor's degree

Tools

Power BI
SQL
Snowflake
Python

Job description

The Wellness Pet Company is seeking a data analytics intern to support the development and enhancement of BI dashboards and data models. You will write SQL queries, assist with data cleansing and ETL processes, and analyze sales and operational data to translate findings into actionable insights.

You will collaborate with cross-functional teams, gain exposure to data governance and modern analytics tools like Power BI, Python, and Snowflake, and contribute to data-driven decision making while

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