Data Operations Engineer

Summary / 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. Powered by JazzHR