Data Operations Engineer

Alliance Franchise Brands - Plymouth, MI

Full-time

Plymouth, MI

Lessors of Nonfinancial Intangible Assets (except Copyrighted Works)

About the position

The Data Operations (DataOps) Engineer is responsible for designing, building, and maintaining data pipelines, storage, and delivery systems to support data-driven initiatives across the franchise network. This role involves ensuring data integrity and security, transforming and visualizing data, advocating for data best practices, and collaborating with various departments to optimize data collection methods. The engineer will also monitor data pipelines, assist with data projects, and create documentation for data elements.

Responsibilities

• Ensure Data Integrity and Security by cleaning and organizing data to ensure accuracy and reliability, and managing data access permissions.
• Transform operational data into insightful reporting and analytics data and create compelling visualizations.
• Advocate Data Best Practices by collaborating with various departments to discover and optimize data collection methods and ensure data quality.
• Identify and work with others to rectify inaccuracies in data to maintain high data quality.
• Develop compliant data sets that adhere to internal and external standards.
• Collaborate across business domains to assist with various data projects.
• Oversee data pipelines and automations to ensure smooth and efficient operations.
• Diagram and document schema, model, lifecycle, and lineage of various data elements.

Requirements

• Degree in Computer Science, Data Science, Information Systems, or a related field plus 2+ years of experience in Data Engineering, Data Science, DevOps, or a related role, or 5+ years of equivalent work experience.
• Proficiency in MS SQL Server (e.g., Indexes, Stored Procedures, and Complex Views).
• Skilled at programming in Python, Scala, TSQL, and/or R.
• Experience with data storage and management solutions (e.g.: Data Warehouses, Data Lakes, and Data Lakehouses).
• Familiarity with ETL/ELT methodologies and tools (e.g., Azure Data Factory and Altova MapForce/FlowForce).
• Knowledge of dimensional data modeling principles and techniques.
• Understanding of efficient schema design, compatibility and evolution practices.
• Expertise in Power BI for data visualization.
• Ability to deliver data into descriptive, diagnostic, predictive, and prescriptive analytics.

Nice-to-haves

• Bachelor's degree preferred.
• Preferred experience in franchising or retail environments.
• Experience with DAX and PowerQuery.
• Working knowledge of Microsoft's Dataverse and Power Platform.