Enterprise Data Operations Assoc Manager

As a member of the data engineering team at PepsiCo, you will play a crucial role in developing and overseeing data product build & operations. Your primary responsibility will be to drive a strong vision for how data engineering can proactively create a positive impact on the business. Working alongside a team of data engineers, you will build data pipelines, rest data on the PepsiCo Data Lake, and facilitate exploration and access for analytics, visualization, machine learning, and product development efforts across the company. Your contributions will directly impact the design, architecture, and implementation of PepsiCo's flagship data products in areas such as revenue management, supply chain, manufacturing, and logistics. You will collaborate closely with process owners, product owners, and business users, operating in a hybrid environment that includes in-house, on-premise data sources as well as cloud and remote systems. Your responsibilities will include active contribution to code development, managing and scaling data pipelines, building automation and monitoring frameworks for data pipeline quality and performance, implementing best practices around systems integration, security, performance, and data management, and empowering the business through increased adoption of data, data science, and business intelligence. Additionally, you will collaborate with internal clients, drive solutioning and POC discussions, and evolve the architectural capabilities of the data platform by engaging with enterprise architects and strategic partners. To excel in this role, you should have at least 6+ years of overall technology experience, including 4+ years of hands-on software development, data engineering, and systems architecture. You should also possess 4+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools, along with expertise in SQL optimization, performance tuning, and programming languages like Python, PySpark, and Scala. Experience in cloud data engineering, specifically in Azure, is essential, and familiarity with Azure cloud services is a plus. You should have experience in data modeling, data warehousing, building ETL pipelines, and working with data quality tools. Proficiency in MPP database technologies, cloud infrastructure, containerized services, version control systems, deployment & CI tools, and Azure services like Data Factory, Databricks, and Azure Machine Learning tools is desired. Additionally, experience with Statistical/ML techniques, retail or supply chain solutions, metadata management, data lineage, data glossaries, agile development, DevOps, DataOps concepts, and business intelligence tools will be advantageous. A degree in Computer Science, Math, Physics, or related technical fields is preferred for this role.,