SWE & App Arch Engineer

PepsiCo•New York, NY

1d•$79,800 - $136,100•Onsite

About The Position

As Data Platform Engineer, you will help build, maintain, and scale the infrastructure and pipelines that form the backbone of our data ecosystem. Working closely with senior engineers, you will gain hands-on experience with the modern data stack, cloud infrastructure, and data orchestration. This role is highly collaborative and perfect for someone with a strong foundation in computer science who is eager to learn, adapt, and write high-quality code.

Requirements

Bachelor’s degree in computer science, Software Engineering, or a related technical field (or equivalent practical/bootcamp experience).
Strong grasp of core Computer Science principles, including object-oriented like Python
Solid understanding of data structures, algorithms, and how to optimize code for performance and scale.
Deep understanding of database architecture, relational concepts, and strong proficiency in SQL.

Nice To Haves

1 to 2 years of experience (including internships, co-ops, or substantial academic/personal projects) in software engineering, data engineering, or DevOps.
Familiarity with Apache Airflow for scheduling/orchestration and dbt for data transformation.
Exposure to Terraform for managing cloud resources.
Basic understanding or hands-on experience with modern data warehouses/lakehouses like Snowflake or Databricks.
Familiarity with Kubernetes and Docker for deploying and managing scalable, containerized applications.
Experience working with PostgreSQL.
Understanding of and experience using AI coding assistants (e.g., Claude, GitHub Copilot) to accelerate development and problem-solving.

Responsibilities

Assist in the design, development, and maintenance of scalable data pipelines and cloud infrastructure
Work alongside data engineers, data scientists, and analysts to understand data needs and ensure reliable data delivery.
Help monitor platform performance, troubleshoot data pipeline failures, and resolve foundational database issues
Embrace AI and modern developer tools to write clean, efficient, and well-documented code
Actively learn new technologies, frameworks, and best practices in the rapidly evolving data engineering space.