Location: Atlanta, GA
Company: Chick-Fil-A
products within the Field Operations Analytics portfolio under the stewardship of the ED&A Service Analytics team within Enterprise Data & Analytics (ED&A). Sr. Lead Data Engineers typically design and implement necessary data engineering on technically complex projects, focusing on developing solutions to data pipelining, data modeling, data accessibility, and/or Data Ops needs.
They must be able to quickly develop mastery of the needed subject across any line of business for which they are responsible. Our Sr. Lead Data Engineers typically work with more latitude for action or decisions on projects that are more complex or cross-functional in nature. They may represent EA in external
conversations and may assist with the selection or oversight of outside vendor partners. They are expected to influence the project execution of partnered IT and analyst teams.
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 our Sr. Lead Data Engineers to have demonstrated fluency and competency in both the technology language of IT and the analytics language of data scientists and insights analysts. They should have experience developing and implementing data models for analytic use
and a moderate level of experience with cloud database architecture.
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. This is a professional track role. Our Flexible Future model offers a healthy mix of working in person and remotely, strengthening key elements of the Chick-fil-A culture by fostering collaboration and community. Responsibilities Exhibit wider latitude in aligning business stakeholders, Insights Analysts, Data Scientists, and IT teams to translate business logic into scalable data and analytic solutions on complex projects Design and build new up-stream production-grade data sources for Data Scientists' use in modeling, integrates data from across the business into modeling pipelines, and builds on-line and off-line feature stores to service both model production and model development activities.
Finds and prepares data for Insights Analysts. Possesses the ability to navigate multiple Data Portfolios across the business, including Locations Data Portfolio, Financials Data Portfolio, and People Data Portfolio Works with Data Scientists to design and implement complex, model-specific feature engineering Partners with DTT Deployment Engineers on complex software engineering solutions for delivering data to and from production model pipelines Actively participates in the Community of Data Engineers (CODE) Designs specific tool implementations, understanding both data visualization, ETL, and cloud compute performance requirements and expectations Manages any needed maintenance and quality control on data pipelines or data products they have built which are actively in use Helps design patterns for efficient use of cloud compute resources 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, including data privacy and data ethics policy requirements Performs ad-hoc analysis as necessary to support specific project work Drives complex projects to success and enables others to own the impact Minimum Qualifications Strong analytical and data modeling skills Deep understanding of database technology Deep understanding of analytic platform data use Strong programming skills in SQL and/or Python Experience developing and implementing data models for analytic use Moderate experience with cloud database architecture Fast learner and proven problem solver Skilled at partnering 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 Keen eye for detail and thoughtful investigation of data Has a steadfast focus on creating impactful change 5 years' experience Preferred Qualifications Some experience using the AWS big data technology stack Extensive experience with Alteryx or similar ETL platforms Extensive experience with Tableau or similar data visualization tools Moderate experience implementing data governance principles Some experience with Model Operations tools and processes in any context 8 years' experience Minimum Years of Experience 5 Travel Requirements 10% Required Level of Education Bachelor's Degree Preferred Level of Education Masters Degree Major/Concentration MIS, Decision Sciences, Engineering, Business Analytics, Computer Science, or other similar fields
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