Data Engineer

One of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse brands.
Data
Mid-Level Software Engineer
Hybrid
5,000+ Employees
5+ years of experience
Enterprise SaaS · Consumer

Description For Data Engineer

PepsiCo is seeking a Data Engineer to join their Data Management and Operations team. This role is crucial in developing and maintaining data pipelines that support PepsiCo's global business scale. The position involves working with enterprise data foundations to enable business insights, advanced analytics, and new product development. As a key technical expert, you'll be responsible for developing data products and operations while working with various source systems in the PepsiCo Data Lake. The role focuses on building solutions for revenue management, supply chain, manufacturing, and logistics.

The ideal candidate will work in a hybrid environment, managing both on-premise and cloud systems. You'll be part of a team that maintains data integrity, enables rapid access to data for decision-making, and supports cross-functional collaboration across the enterprise. The position requires strong technical skills in data engineering, cloud technologies (particularly Azure), and programming languages like Python and SQL.

PepsiCo offers a dynamic work environment with over 250,000 employees globally and a strong commitment to sustainability and ethical business practices. The company operates in more than 200 countries with 22 billion-dollar brands. This role provides an opportunity to work on large-scale data projects that directly impact business operations and innovation.

The position requires excellent communication skills, the ability to work with senior management, and a strong understanding of both technical and business requirements. You'll be expected to contribute to code development, manage data pipelines, and work closely with data science and product teams to drive solutions.

Last updated 17 minutes ago

Responsibilities For Data Engineer

  • Manage and scale data pipelines from internal and external data sources
  • Build and own automation and monitoring frameworks for data pipeline quality
  • Develop and optimize procedures to productionalize data engineering pipelines
  • Define and manage SLAs for data products and processes
  • Support large-scale experimentation for data scientists
  • Create documentation and reusable packages/libraries
  • Collaborate with data science and product teams

Requirements For Data Engineer

Python
Kubernetes
  • 5+ years of overall technology experience with 2+ years in software development and data engineering
  • 2+ years experience in SQL optimization and programming languages (Python, PySpark, Scala)
  • 1+ years in Azure cloud data engineering
  • Experience with version control systems and CI tools
  • Experience with data modeling and data warehousing
  • BE/B Tech in Computer Science, Math, Physics, or other technical fields
  • Experience with business intelligence tools like PowerBI
  • Working knowledge of agile development, DevOps and DataOps

Benefits For Data Engineer

Relocation Benefits
  • Relocation Eligible - Standard

Interested in this job?

Jobs Related To PepsiCo Data Engineer

Data Engineer

Data Engineer role at PepsiCo focused on building and maintaining data pipelines and infrastructure for analytics and machine learning.

Data Scientist

Data Scientist position at Mastercard focusing on economic insights and forecasting using transaction data analysis and machine learning.

Data Engineer

Data Engineer role at PepsiCo focused on building and maintaining data pipelines and infrastructure for analytics and machine learning.

Data Integration Developer

Data Integration Developer position at Reach, focusing on implementing and managing data integration solutions for financial reconciliation and reporting in a hybrid work environment.

Data Engineer, Amazon Customer Service

Data Engineer position at Amazon Customer Service focusing on building and maintaining data pipelines for defect detection and customer experience improvement.