SWE & App Arch Engineer

Overview 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.

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

The expected compensation range for this position is between $79,800 - $136,100. 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. Bonus based on performance and eligibility target payout is 5% of annual salary paid out annually. 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 Required Qualifications

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

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

> 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