How We Work At Chick-fil-A
Chick-fil-A, Inc. ('Chick-fil-A' or 'the Company') Staff members play a vital role in achieving our strategic goals by developing their skills, fostering inclusive teamwork, and embracing innovation. All Staff are expected to contribute to a compelling future by inspiring and motivating those around them. Growth and development are essential at Chick-fil-A. We want Staff to seek new perspectives and adopt new methods to drive continuous improvement and adaptation to evolving business needs. Lastly, we ask Staff to seek wisdom, expect the best, accept responsibility, respond with courage, and think others first.
Our Flexible Futures Model offers a healthy mix of working in person (currently a minimum of 8-10 days per month) and virtually, strengthening key elements of the Chick-fil-A culture by fostering collaboration and community.
Overview
As a Sr. Lead Data Engineer within the Field Insights & Technology team, you will be responsible for leading and executing complex data engineering project work in support of multiple Restaurant Development analytics and reporting needs. Sr. Lead Data Engineers typically design, implement, maintain, and optimize necessary analytics infrastructure on technically complex projects, focusing on developing solutions to data modeling and/or analytics technology needs. They must be able to quickly develop mastery of the needed subject across Restaurant Development for which they are responsible.
Our Sr. Lead Data Engineers typically work with some latitude for action or decisions on specific projects, solutions, or technical issues. Successful candidates for this role must have strong analytical and data modeling skills, a deep understanding of database technology and data use within analytic platforms, and they must have strong programming skills with SQL and/or Python. We expect Sr. Lead Data Engineers to have the capacity for fluency and competency in both the technology language of IT and the analyst language of departmental analysts. They will need to be fast learners with a keen eye for detail, systems thinking, and process design. They must be team players who work steadfastly to create impactful change.
Responsibilities
- The person who fills this role will be expected to do the following as a part of their regular work responsibilities:
- Works with business stakeholders and IT to translate business logic into scalable data and analytic solutions.
- Develops ETL pipelines for general business consumption, typically leveraging existing patterns as available for specific project execution and building pipelines with scalability in mind.
- Leverages cloud compute resources efficiently.
- Owns and is accountable for data model and code quality and any relevant documentation.
- Implements data governance and master data management principles across specific project execution.
- Performs ad-hoc analysis as necessary to support specific project work.
- Drives complex projects to success and enables others to own the impact
- Manages any needed maintenance and quality control on data pipelines or data products they have built which are actively in use
Required Qualifications (Knowledge, Skills, & Abilities)
- Has strong analytical and BI data modeling skills
- Has a deep understanding of database technology
- Has a deep understanding of analytic platform data use
- Has some experience with DBT and/or other ETL/data transformation tools
- Strong programming skills in SQL and/or Python
- Has some experience using the AWS big data technology stack and console
- Has the skill to partner with cross-functional teams using strong written and verbal communication
- Keen eye for system thinking and process design, especially with respect to scalability and automation
Preferred Qualifications (Knowledge, Skills, & Abilities)
- Has extensive experience with Databricks or similar ETL platforms
- Has extensive experience with DBT or similar data transformation tools
- Has moderate experience implementing data governance principles
- Proficiency in Data Analysis, AWS Redshift, AWS S3, SQL, Python, Tableau preferred
- Has moderate experience using the AWS big data technology stack and console
- Has experience architecting data pipelining solutions and data infrastructure
Required Years Of Experience
4
Preferred Years Of Experience
5
Travel Requirements
10%
Required Level Of Education
Bachelor's degree or equivalent experience
Preferred Level Of Education
Master's Degree
Required Major/Concentration
MIS, Decision Sciences, Engineering, Business Analytics, Computer Science, or other similar fields
Relocation Assistance Provided
No