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