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# Analytics Platform Engineer

- **Company:** PepsiCo, Inc.
- **Location:** New York, NY, United States
- **Experience:** Starter
- **Salary:** $79,800.0 - $136,100.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Airflow, BigQuery, Continuous Integration, Information Engineering, Github, Power BI, Cloud Services, Tableau (Software), Workflow Management Systems, Macros, Delivery Pipeline, Large Language Models, Snowflake, Git, Git Flow, Data Management, Data Delivery, Software Version Control, Data Pipelines, Jenkins, Databricks
- **Published:** September 10, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=17e2fb702c156b62

## About the Role

* 1-2 years of experience (including internships, co-ops, or substantial academic/personal projects)
 * Familiarity with dbt or similar transformation frameworks
 * Familiarity with Apache Airflow or similar orchestration tools
 * Experience with CI/CD systems (GitHub Actions, Jenkins, or equivalent)
 * Exposure to BI platforms (Power BI, Tableau, or equivalent)
 * Exposure to large language models and their application to analytics workflows
 * Experience with version control (Git) and branching strategies
 * Familiarity with cloud data platforms (Snowflake, BigQuery, or Databricks)

## Description

* Develop and maintain the dbt project infrastructure - including CI/CD workflows, project configuration, macros, and testing frameworks - that delivery engineering teams build upon
 * Build and support Apache Airflow orchestration infrastructure, ensuring reliable scheduling, monitoring, and scalability for data pipelines
 * Maintain and evolve the CI/CD platform (GitHub Actions workflows, pre-commit hooks, automated validation) that enforces quality and deployment standards
 * Manage and administer the Power BI platform - including workspace governance, capacity management, and deployment pipelines - to support report delivery teams
 * Develop and maintain metadata collection systems for tracking pipeline health, lineage, and model ownership
 * Define and enforce best practices, patterns, and conventions across data delivery and report delivery engineering teams
 * Support evaluation and prototyping of AI-for-BI capabilities, including automated insight generation using large language models
 * Research and evaluate emerging tools and technologies; present findings and recommendations to inform platform direction
 * Participate in build-vs-buy assessments and contribute to tooling decisions that delivery engineering teams depend on
 * Collaborate with engineering teams to identify platform gaps, gather requirements, and deliver scalable solutions