Data Operations Engineer

3 months ago

Huntington Woods, United States Alliance Franchise Brands Full time
Job DescriptionJob DescriptionSummary/objective
The Data Operations (DataOps) Engineer plays a crucial role in designing, building, and maintaining data pipelines, storage and delivery systems to support various data-driven initiatives across our franchise network. They must also be able to contribute to accurate and timely reports and visualizations. This role is part of a dynamic team of information and technology professionals working closely with stakeholders to understand business requirements and translate them into scalable data solutions.     

Essential functions
  • Ensure Data Integrity and Security: Clean and organize data to ensure accuracy and reliability and manage data access permissions to maintain security and compliance.
  • Transform and Visualize Data: Transform operational data into insightful reporting and analytics data and create compelling visualizations.
  • Advocate Data Best Practices: Collaborate with various departments to discover and optimize data collection methods, ensure data quality, and support a data-driven culture within AFB.
  • Proactive Data Correction: Identify and work with others to rectify inaccuracies in data to maintain high data quality.
  • Develop Compliant Data Sets: Work with teams to develop data sets that comply with internal and external standards.
  • Assist with Data Projects: Collaborate across business domains to assist with various data projects.
  • Monitor Data Pipelines: Oversee data pipelines and automations to ensure smooth and efficient operations.
  • Create Usable Documentation: Diagram and document schema, model, lifecycle, and lineage of various data elements.

Competencies
  • Excellent multitasking abilities.
  • Strong collaboration and teamwork skills.
  • High level of self-driven motivation and accountability.
  • Creativity in problem-solving and data visualization.
  • Ability to communicate effectively with both technical and non-technical stakeholders.

Work environment
  • Professional corporate and team-oriented environment
  • Hybrid work schedule with at least 2 days each week in office

Physical demands
  • Prolonged periods sitting at a desk and working on a computer.
  • Must be able to lift up to 15 pounds at times.

Travel requirements
  • Minimal travel if any

Required education and experience
  • 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.

Preferred education and experience
  • 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.

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