Job Description

Overview The Quick Cycle Innovation team is a group within PepsiCo whose mission is to create and nurture new-to-the-world brands by leveraging relevant PepsiCo resources and building new capabilities for the company. Our underlying Quick Cycle Innovation (QCI) methodology is the foundation of our work, and a muscle we are continuing to evolve and improve - for our own team and broader PepsiCo Innovation Teams. Within QCI, the Data & Analytics team is responsible for grounding the team in \'science\' using data as the default arbiter of debate. Job Summary In this role, you will be on the ground floor of data engineering for our innovation analytics - piping large data sets into our QCI centralized dashboard hub. These tools will broadly facilitate data-driven decisions and direction for PepsiCo\'s innovation agenda. Your day-to-day will revolve around extracting, ingesting and manipulating data from a variety of different data sources in the CPG food & beverage ecosystem. These data feeds will enable the Insights & Analytics team to develop dashboards/visualizations that unlock opportunities for breakout innovation. Responsibilities Act as a consultant to the broader business users, management, vendors, and technicians to determine technology needs and system requirements Unlock sources of data that impact PepsiCo\'s innovation agenda from ideation through in-market execution Design and implement data infrastructure and processing workflows required to support data science, machine learning, BI and reporting Build robust, efficient and reliable data pipelines consisting of diverse data sources Design and develop real time streaming and batch processing pipeline solutions Own the data expertise and data quality for the pipelines Drive the collection of new data and refinement of existing data sources Identify shared data needs and data sources, understand their specific requirements, and build efficient and scalable pipelines to meet various needs Combine and manipulate data sources to produce value-added analyses from which insights and opportunities can be extracted Run and build custom algorithms/models (e.g. regressions) to uncover trends and insights Qualifications BS or MS degree in Computer Science or a related technical field 4+ years of Python or Java development experience Experience with multiple data technologies and concepts such as SQL, NoSQL, Airflow, Kafka, Hadoop, Hive, Spark, MapReduce and Columnar databases 4+ years of experience with schema design and dimensional data modeling Ability in managing and communicating data warehouse plans to internal clients Experience designing, building and maintaining data processing systems Experience with specific AWS technologies (such as Glue, S3, Redshift, EMR, and Kinesis) Experience writing production code for Python or JVM-based systems, but you know a few other languages and like the right tool for the job Familiarity of machine-learning tools and techniques Experience optimizing larger applications to increase speed, scalability, and extensibility Structured thinker / problem solver Comfort with ambiguity as demonstrated by being able to adapt in less-structured environments Voices opinions fearlessly self-starter

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