Senior Data Engineer
The Coca-Cola CompanyAbout the role
Location(s):
United States of AmericaCity/Cities:
AtlantaTravel Required:
00% - 25%Relocation Provided:
NoJob Posting End Date:
January 28, 2026Shift:
Job Description Summary:
About Us
CPS (Commercial Products Supply) is a key part of the Advantaged Supply Chain of the Technical Function of The Coca-Cola Company. CPS manufactures concentrates and beverage bases for sale to bottling partners all over the world. This global organization manages a network of 19 manufacturing plants in 18 different countries along with 2 office locations (Atlanta & Drogheda, Ireland). CPS also manages complex additional materials supply chains (e.g. juice, coffee, tea, milk, etc.) on behalf of bottling partners.
The Senior Data Engineer will be responsible for the design, development, and operational excellence of the CPS data platform across global plant operations and supply networks. This role provides hands-on technical leadership, architectural ownership, and strategic partnership while remaining actively involved in data engineering, code reviews, and production support. This role enables scalable, reliable, and secure data solutions that support data-driven decision-making across global plant operations and supply networks.
Function Related Activities / Key Responsibilities
Serve as the senior-most individual contributor and subject matter expert for data engineering solutions across CPS
Own the technical architecture, design decisions, and implementation of the CPS data platform
Design, develop, and optimize data pipelines using Azure Data Factory (ADF)
Build and maintain high-performance, scalable data transformations using PySpark, SQL, and Python
Actively contribute code and review/approve pull requests, setting quality and engineering standards
Define, enforce, and evolve data engineering best practices, standards, and architectural patterns
Partner with CPS stakeholders, plant teams, and analytics partners to translate business needs into technical solutions
Lead technical design reviews and provide mentorship and guidance to engineers without direct people management
Ensure data quality, reliability, monitoring, observability, and performance of production data pipelines
Influence roadmap planning, estimation, and prioritization for data engineering initiatives
Drive simplification, standardization, and long-term maintainability of data pipelines
Functional Skills
Expert-level proficiency in Python, SQL, and PySpark
Hands-on experience with Databricks, Snowflake, or similar analytics platforms
Strong understanding of data warehousing concepts, analytical modeling, and performance optimization
Expertise in orchestration frameworks such as Azure Data Factory (ADF), AWS Glue, or similar
Deep understanding of data architecture, ETL/ELT design, and scalable data modeling
Experience with cloud-native platforms, CI/CD, and DevOps practices
Familiarity with data observability, lineage, and monitoring tooling
Ability to provide technical leadership through code, reviews, and design guidance
Excellent critical thinking, analytical and problem-solving skills
Related Work Experience
5+ years of experience in data engineering, analytics engineering, or software engineering
Experience supporting data platforms for manufacturing, supply chain, or operations environments strongly preferred
Proven experience designing and scaling cloud-based data platforms, ideally on Microsoft Azure
Education Requirements
Bachelor’s degree in computer science, Engineering, or a related technical field required
Master’s degree preferred
Skills:
Analytics, Building Architecture, Business Intelligence (BI), Data Architecture, Data Modeling, Data Warehousing (DW), Microsoft Azure, Programming Languages, PySpark, Python (Programming Language), Structured Query Language (SQL)Pay Range:
$159,600 - $187,215Base pay
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