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.
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Transform and Visualize Data: Transform operational data into insightful reporting and analytics data and create compelling visualizations.
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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.
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Proactive Data Correction: Identify and work with others to rectify inaccuracies in data to maintain high data quality.
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Develop Compliant Data Sets: Work with teams to develop data sets that comply with internal and external standards.
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Assist with Data Projects: Collaborate across business domains to assist with various data projects.
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Monitor Data Pipelines: Oversee data pipelines and automations to ensure smooth and efficient operations.
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Create Usable Documentation: Diagram and document schema, model, lifecycle, and lineage of various data elements.
Competencies-
Excellent multitasking abilities.
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Strong collaboration and teamwork skills.
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High level of self-driven motivation and accountability.
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Creativity in problem-solving and data visualization.
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Ability to communicate effectively with both technical and non-technical stakeholders.
Work environment-
Professional corporate and team-oriented environment
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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.
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Must be able to lift up to 15 pounds at times.
Travel requirements
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.
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Proficiency in MS SQL Server (e.g., Indexes, Stored Procedures, and Complex Views).
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Skilled at programming in Python, Scala, TSQL, and/or R.
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Experience with data storage and management solutions (e.g.: Data Warehouses, Data Lakes, and Data Lakehouses)
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Familiarity with ETL/ELT methodologies and tools (e.g., Azure Data Factory and Altova MapForce/FlowForce).
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Knowledge of dimensional data modeling principles and techniques.
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Understanding of efficient schema design, compatibility and evolution practices
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Expertise in Power BI for data visualization.
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Ability to deliver data into descriptive, diagnostic, predictive, and prescriptive analytics.
Preferred education and experience-
Bachelor's degree preferred.
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Preferred experience in franchising or retail environments.
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Experience with DAX and PowerQuery.
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Working knowledge of Microsoft’s Dataverse and Power Platform.
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