Chick-fil-A
Senior Data Engineer, Supply Chain Optimization
Chick-fil-A, Atlanta, Georgia, United States, 30383
Overview
We are looking for a passionate and detail-oriented Senior Data Engineer to be an essential member of our Data Architecture and Master Data Management (MDM) team. In this role, you will analyze, document, and enhance the flow of data throughout our organization. Your efforts will ensure that our data accurately reflects and supports our physical processes and systems.
You will play a vital part in designing and implementing improvements to our data lifecycle management and facilitate integration between operational processes and analytics. Utilizing your expertise in Industrial Engineering, Process Engineering, and Systems Engineering methodologies, you will design and optimize business processes and their integration with data.
Our Flexible Future model promotes a balanced blend of in-person and virtual work, which fosters collaboration and strengthens the values of our company culture.
Responsibilities
Process Engineering:
Conduct requirements gathering and promote a strong understanding of processes, documentation, and policy design. You will align the digital data environment with the physical network it informs.
Map current state processes, identify inefficiencies, and design improved future state processes. Utilize business process modeling and notation proficiency (e.g., BPMN). Apply strong analytical and problem-solving skills to address root causes of process issues. Facilitate workshops and gather requirements from stakeholders effectively. Implement process improvement methodologies (e.g., Lean, Six Sigma). Translate business requirements into technical specifications. Leverage data analysis to advocate for process improvement recommendations. Understand data governance and data quality principles.
Systems Engineering:
Design, implement, and maintain data and analytics systems. Have a solid understanding of data warehousing, data lakes, and ETL processes. Exhibit proficiency in cloud-based data platforms (e.g., AWS, Azure, GCP). Employ data modeling and database design knowledge. Understand data integration techniques and tools. Troubleshoot system issues and provide solutions. Understand system security and data privacy principles. Utilize DevOps practices and automation.
Process Observation and Documentation:
Analyze how our digital data ecosystem reflects physical processes and systems. Document data flows and integration flows using best practice techniques (e.g., process flow diagrams, data flow diagrams).
Current State Assessment:
Thoroughly document current data flows and physical processes related to data creation and consumption. Identify pain points and areas for improvement.
Target State Design:
Design an optimal target state for data flows that align with business objectives. Develop comprehensive data lifecycle management strategies for the MDM system.
Gap Analysis:
Conduct detailed gap analysis to identify steps needed to achieve future state designs. Present recommendations for bridging identified gaps.
Data Lifecycle Management:
Focus on data creation, ingestion, systematization, consumption, and deprecation within MDM. Develop strategies to enhance data quality, governance, and compliance.
Operational Process and Analytics Unification:
Identify opportunities to unify analytics with operational processes. Design and implement solutions for seamless integration.
Collaboration and Communication:
Work closely with data architects, data engineers, business analysts, and other stakeholders. Communicate findings and project updates to both technical and non-technical audiences.
Minimum Qualifications Bachelor's Degree in Engineering (industrial or systems preferred), Computer Science, Information Systems, or a related field. 4+ years of relevant experience. Strong knowledge of data architecture principles and data governance practices. Experience with data modeling and integration techniques. Proficiency in process mapping and documentation tools. Excellent analytical, problem-solving, and communication skills. Able to work independently and collaboratively in a dynamic environment. Preferred Qualifications 5+ years of relevant experience. Minimum Years of Experience:
4 Travel Requirements:
10% Required Level of Education:
Bachelor's Degree Major/Concentration:
Engineering (industrial or systems preferred), Computer Science, Information Systems, or related field.
Conduct requirements gathering and promote a strong understanding of processes, documentation, and policy design. You will align the digital data environment with the physical network it informs.
Map current state processes, identify inefficiencies, and design improved future state processes. Utilize business process modeling and notation proficiency (e.g., BPMN). Apply strong analytical and problem-solving skills to address root causes of process issues. Facilitate workshops and gather requirements from stakeholders effectively. Implement process improvement methodologies (e.g., Lean, Six Sigma). Translate business requirements into technical specifications. Leverage data analysis to advocate for process improvement recommendations. Understand data governance and data quality principles.
Systems Engineering:
Design, implement, and maintain data and analytics systems. Have a solid understanding of data warehousing, data lakes, and ETL processes. Exhibit proficiency in cloud-based data platforms (e.g., AWS, Azure, GCP). Employ data modeling and database design knowledge. Understand data integration techniques and tools. Troubleshoot system issues and provide solutions. Understand system security and data privacy principles. Utilize DevOps practices and automation.
Process Observation and Documentation:
Analyze how our digital data ecosystem reflects physical processes and systems. Document data flows and integration flows using best practice techniques (e.g., process flow diagrams, data flow diagrams).
Current State Assessment:
Thoroughly document current data flows and physical processes related to data creation and consumption. Identify pain points and areas for improvement.
Target State Design:
Design an optimal target state for data flows that align with business objectives. Develop comprehensive data lifecycle management strategies for the MDM system.
Gap Analysis:
Conduct detailed gap analysis to identify steps needed to achieve future state designs. Present recommendations for bridging identified gaps.
Data Lifecycle Management:
Focus on data creation, ingestion, systematization, consumption, and deprecation within MDM. Develop strategies to enhance data quality, governance, and compliance.
Operational Process and Analytics Unification:
Identify opportunities to unify analytics with operational processes. Design and implement solutions for seamless integration.
Collaboration and Communication:
Work closely with data architects, data engineers, business analysts, and other stakeholders. Communicate findings and project updates to both technical and non-technical audiences.
Minimum Qualifications Bachelor's Degree in Engineering (industrial or systems preferred), Computer Science, Information Systems, or a related field. 4+ years of relevant experience. Strong knowledge of data architecture principles and data governance practices. Experience with data modeling and integration techniques. Proficiency in process mapping and documentation tools. Excellent analytical, problem-solving, and communication skills. Able to work independently and collaboratively in a dynamic environment. Preferred Qualifications 5+ years of relevant experience. Minimum Years of Experience:
4 Travel Requirements:
10% Required Level of Education:
Bachelor's Degree Major/Concentration:
Engineering (industrial or systems preferred), Computer Science, Information Systems, or related field.