Overview PepsiCo operates in an environment undergoing immense and rapid change. Big data and digital technologies are driving business transformation that is unlocking new capabilities and business innovations in areas like eCommerce, mobile experiences, and IoT. The key to winning in these areas is leveraging enterprise data foundations built on PepsiCo’s global business scale to enable business insights, advanced analytics, and new product development. PepsiCo’s Data Management and Operations team is tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations, and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation. Responsibilities As a member of the data engineering team, you will be the key technical expert developing and overseeing PepsiCos data product build &amp; operations and driving a strong vision for how data engineering can proactively create a positive impact on the business. Youll be an empowered member of a team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help lead the development of very large and complex data applications into public cloud environments, directly impacting the design, architecture, and implementation of PepsiCos flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. You will work closely with process owners, product owners, and business users. Youll be working in a hybrid environment with in-house, on-premise data sources, as well as cloud and remote systems. Accountabilities: Own data pipeline development end-to-end, spanning data modeling, testing, scalability, operability, and ongoing metrics. Ensure that we build high-quality software by reviewing peer code check-ins. Define best practices for product development, engineering, and coding as part of a world-class engineering team. Collaborate in architecture discussions and architectural decision-making that is part of continually improving and expanding these platforms. Lead feature development in collaboration with other engineers; validate requirements/stories, assess current system capabilities, and decompose feature requirements into engineering tasks. Focus on delivering high-quality data pipelines and tools through careful analysis of system capabilities and feature requests, peer reviews, test automation, and collaboration with other engineers. Develop software in short iterations to quickly add business value. Introduce new tools/practices to improve data and code quality; this includes researching/sourcing 3rd party tools and libraries, as well as developing tools in-house to improve workflow and quality for all data engineers. Support data pipelines developed by your team through good exception handling, monitoring, and, when needed by debugging production issues. Compensation and Benefits: The expected compensation range for this position is between $64,900 - $132,550. Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process. A business development incentive equity may be awarded based on eligibility and performance. Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement. In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan. Qualifications 4+ years of overall technology experience that includes at least 3+ years of hands-on software development, data engineering, and systems architecture. 3+ years of experience in SQL optimization and performance tuning. Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with data profiling and data quality tools like Apache Griffin, Deequ, or Great Expectations. Current skills in the following technologies: Python Orchestration platforms: Airflow, Luigi, Databricks, or similar. Relational databases: Postgres, MySQL, or equivalents. MPP data systems: Snowflake, Redshift, Synapse, or similar. Cloud platforms: AWS, Azure, or similar. Version control (e.g., GitHub) and familiarity with deployment, CI/CD tools. Fluent with Agile processes and tools such as Jira or Pivotal Tracker. Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes is a plus. Understanding of metadata management, data lineage, and data glossaries is a plus. EEO Statement Our Company will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the Fair Credit Reporting Act, and all other applicable laws, including but not limited to, San Francisco Police Code Sections 4901-4919, commonly referred to as the San Francisco Fair Chance Ordinance; and Chapter XVII, Article 9 of the Los Angeles Municipal Code, commonly referred to as the Fair Chance Initiative for Hiring Ordinance. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. PepsiCo is an Equal Opportunity Employer: Female / Minority / Disability / Protected Veteran / Sexual Orientation / Gender Identity / Age. If youd like more information about your EEO rights as an applicant under the law, please download the available EEO is the Law &amp; EEO is the Law Supplement documents. View PepsiCo EEO Policy. Please view our Pay Transparency Statement. As a member of the data engineering team, you will be the key technical expert developing and overseeing PepsiCos data product build &amp; operations and driving a strong vision for how data engineering can proactively create a positive impact on the business. Youll be an empowered member of a team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help lead the development of very large and complex data applications into public cloud environments, directly impacting the design, architecture, and implementation of PepsiCos flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. You will work closely with process owners, product owners, and business users. Youll be working in a hybrid environment with in-house, on-premise data sources, as well as cloud and remote systems. Accountabilities: Own data pipeline development end-to-end, spanning data modeling, testing, scalability, operability, and ongoing metrics. Ensure that we build high-quality software by reviewing peer code check-ins. Define best practices for product development, engineering, and coding as part of a world-class engineering team. Collaborate in architecture discussions and architectural decision-making that is part of continually improving and expanding these platforms. Lead feature development in collaboration with other engineers; validate requirements/stories, assess current system capabilities, and decompose feature requirements into engineering tasks. Focus on delivering high-quality data pipelines and tools through careful analysis of system capabilities and feature requests, peer reviews, test automation, and collaboration with other engineers. Develop software in short iterations to quickly add business value. Introduce new tools/practices to improve data and code quality; this includes researching/sourcing 3rd party tools and libraries, as well as developing tools in-house to improve workflow and quality for all data engineers. Support data pipelines developed by your team through good exception handling, monitoring, and, when needed by debugging production issues. Compensation and Benefits: The expected compensation range for this position is between $64,900 - $132,550. Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process. A business development incentive equity may be awarded based on eligibility and performance. Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement. In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan. 4+ years of overall technology experience that includes at least 3+ years of hands-on software development, data engineering, and systems architecture. 3+ years of experience in SQL optimization and performance tuning. Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with data profiling and data quality tools like Apache Griffin, Deequ, or Great Expectations. Current skills in the following technologies: Python Orchestration platforms: Airflow, Luigi, Databricks, or similar. Relational databases: Postgres, MySQL, or equivalents. MPP data systems: Snowflake, Redshift, Synapse, or similar. Cloud platforms: AWS, Azure, or similar. Version control (e.g., GitHub) and familiarity with deployment, CI/CD tools. Fluent with Agile processes and tools such as Jira or Pivotal Tracker. Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes is a plus. Understanding of metadata management, data lineage, and data glossaries is a plus.