IQ Workforce is a leading recruiting firm for the engineering, analytics, and data science communities.

Our client, Yum!, is a global restaurant company, which engages in the development and operation of some of the most recognizable brands in the world. They have over 30,000 employees and operate over 40,000 restaurants in 135 nations and territories.

Yum! is in the early stages of building out a new center of excellence (COE) for engineering and data science. They are making this investment to help optimize with digital channels and technology innovations with the end goal of creating competitive advantages for their restaurants around the globe.

One of the immediate needs is for Data Engineers who love working with modern data integration frameworks, big data and cloud technologies. Candidates must also be proficient with data programming languages (e.g., Python and SQL). The Data Engineer will build a variety of data pipelines and models to support advanced AI/ML analytics projects – with the intent of elevating the customer experience and driving revenue and profit growth in our restaurants globally.

Responsibilities include:
Partner with KFC, Pizza Hut, & Taco Bell to identify opportunities to leverage company data to drive business outcomes

Play key role in our advance analytics team developing data science solutions, responsible for driving Yum Growth

Develop and maintain global data models by analyzing use cases and applications at Yum! and across our brands (KFC, Pizza Hut and Taco Bell).

Design and develop scalable data ingestion frameworks to transform a variety of large data sets.

Own end-to-end delivery of raw and trained data sets to and from brand cloud environments.

Integrate with Yum! data platform architecture by building applications using open-source frameworks such as Apache Spark, containerized applications (i.e. Kubernetes), and Apache Airflow.

Build and maintain data integration utilities, data scheduling and monitoring capabilities, source-to-target mappings and data lineage trees.

Implement and manage production support processes around data lifecycle, data quality, coding utilities, storage, reporting and other data integration points.

Maintain system performance by identifying and resolving production and application development problems; calculating optimum values for parameters; evaluating, integrating and installing new releases; performing routine maintenance; and answering user questions.

Lead technical teams and projects to deliver projects and accomplish business and IT objectives.

Qualifications:
3-5+ years of data engineering and data warehousing experience.

3-5+ years of experience working in technical project teams and delivering outcomes.

1-2+ years of experience building cloud data solutions (e.g. on Azure, AWS, GCP) and using services such as storage, virtual machines, serverless technologies and parallel processing technologies. Cloud certifications are a plus.

Deep experience with designing and deploying end-to-end solutions with cloud analytic services including storage, elastic computing, databases, serverless technologies, microservices, and AI/ML frameworks.

Deep experience with open-source tools such as Kubernetes, Apache Airflow and Apache Spark.

Background in data with experience in architecture, data modeling, data engineering or data governance using all types of databases.

Working knowledge of agile development, including DevOps concepts.

Experience with cloud SDKs and programmatic access services.

Proficiency in a relevant data/development language for cloud platforms (e.g., R, Python, Java and C#/Unix).

Proficiency in SQL.

Bachelor’s degree from an accredited institution is required.