Data Analytics Engineer

Shamrock Foods - Phoenix, AZ

Full-time - Mid Level

Phoenix, AZ

251-500 employees

Warehousing and Storage

About the position

The position involves developing effective business intelligence strategies and analytics solutions aimed at solving complex business problems and facilitating data-driven decision-making. The successful candidate will apply software engineering and DataOps best practices to establish reusable data assets and analytical data capabilities, which include version control, unit testing, continuous integration, and delivery. The role also requires transforming data to support various analytical use cases and establishing universal data governance policies, rules, standards, and metrics while maintaining comprehensive documentation, lineage, and definitions. Additionally, the candidate will be responsible for training and enabling business users and data workers in the use of enterprise data visualization and BI reporting tools. Other duties may be assigned as necessary.

Responsibilities

• Develop effective business intelligence strategies and analytics solutions to solve complex business problems.
• Apply software engineering and DataOps best practices to establish reusable data assets and analytical data capabilities.
• Transform data to support analytical use-cases.
• Establish universal data governance policies, rules, standards, and metrics while maintaining documentation, lineage, and definitions.
• Train and enable business users and data workers with enterprise data visualization and BI reporting tools.
• Perform other duties as assigned.

Requirements

• Bachelor's or master's degree in Statistics, Mathematics, Computer Science, Software Engineering, or Analytics.
• 4+ years' experience delivering Business Intelligence and analytics at enterprise scale.
• 4+ years' experience with modern BI and Data tools like Power BI, Tableau, Looker, etc.
• 2+ years' experience with cloud data platforms like Databricks, Snowflake, AWS, GCP, or Azure.
• Advanced level SQL for data transformations, queries, and data modeling.
• Expertise with Git or other commonly used version control systems.
• Strong background with advanced data languages like Python, R, or SAS.

Nice-to-haves

• Flexibility to work the demands of the department, which may include evenings, weekends, and holidays.

Benefits

• Health insurance coverage paid for by the company, allowing employees to take home more of their paycheck.
• 401(k) Savings Plan.
• Profit Sharing.
• Paid Time Off.
• Growth opportunities.
• Continued education.
• Wellness programs.