Sr. Lead Data Engineer, Supply Chain

Overview

We are seeking a highly motivated and detail-oriented Process Engineer to join our Data Architecture and Master Data Management (MDM) team. In this role, you will be responsible for analyzing, documenting, and optimizing the flow of data within our organization, ensuring it accurately reflects and supports our physical processes and systems. You will play a key role in designing and implementing improvements to our data lifecycle management and integration between operational processes and analytics. Additionally, you’ll leverage Industrial Engineering, Process Engineering, and Systems Engineering methodologies to design and optimize business process, and how it integrates with data.

 

Our Flexible Future model offers a healthy mix of working in person and virtually, strengthening key elements of the Chick-fil-A culture by fostering collaboration and community. 

Responsibilities

• Process Engineering: Encourage requirements gathering, strong process understanding, documentation, and policy design and enforcement to align the digital data environment and process to the physical network it informs and supports
  • Experience mapping current state processes, identifying inefficiencies, and designing improved future state processes
  • Proficiency in business process modeling and notation (e.g., BPMN)
  • Strong analytical and problem-solving skills to identify root causes of process issues
  • Ability to facilitate workshops and gather requirements from stakeholders
  • Experience in process improvement methodologies (e.g., Lean, Six Sigma)
  • Ability to translate business requirements into technical specifications
  • Experience with data analysis to drive process improvement recommendations
  • Understanding of data governance and data quality principles
• Systems Engineering:
  • Experience in designing, implementing, and maintaining data and analytics systems
  • Strong understanding of data warehousing, data lakes, and ETL processes
  • Proficiency in cloud-based data platforms (e.g., AWS, Azure, GCP)
  • Experience with data modeling and database design
  • Knowledge of data integration techniques and tools
  • Ability to troubleshoot system issues and identify solutions
  • Understanding of system security and data privacy principles
  • Experience with DevOps practices and automation
• Process Observation and Documentation:
  • Observe and analyze how our digital data ecosystem mirrors physical processes and systems
  • Document data flows, information flows, and integration flows using engineering best-practice documentation techniques (e.g., process flow diagrams, data flow diagrams)
• Current State Assessment:
  • Thoroughly assess and document the current state of data flows and physical processes related to data creation, ingestion, systematization, consumption, and deprecation
  • Identify pain points, inefficiencies, and areas for improvement within existing data processes
• Target State Design:
  • Design an optimal target state for data flows and physical processes, aligned with business objectives and industry best practices
  • Develop comprehensive data lifecycle management strategies for the MDM system and analytical data model
• Gap Analysis:
  • Perform detailed gap analysis between current state and target state designs, identifying the steps and resources needed to achieve the desired future state
  • Develop and present recommendations for bridging identified gaps
• Data Lifecycle Management:
  • Focus on how data is created, ingested, systematized, consumed, and deprecated within the MDM system and the analytical data model
  • Develop and implement strategies to improve data quality, governance, and compliance throughout the data lifecycle
• Operational Process and Analytics Unification:
  • Assess opportunities to unify disjointed analytics with their corresponding operational processes
  • Design and implement solutions that enable seamless integration between operational systems and analytical platforms
• Collaboration and Communication:
  • Collaborate closely with data architects, data engineers, business analysts, and other stakeholders to ensure alignment and effective implementation of data solutions
  • Communicate findings, recommendations, and project status 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 related experience
• Strong understanding of data architecture principles, master data management concepts, and data governance practices
• Experience with data modeling, data integration, and data warehousing techniques
• Proficiency in process mapping and documentation tools
• Excellent analytical, problem-solving, and communication skills
• Ability to work independently and collaboratively in a fast-paced environment

Preferred Qualifications

• 5+ years of related 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 a related field