Senior Data Engineer

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

• 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

• 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

• Bachelor's degree in computer science, Engineering, or a related technical field required
• Master's degree preferred