Job description

Are you a current Associate? To be considered, you must submit your application through the internal Career Portal (Jobs Hub). Click here to access. Time Type: Full time Remote Type: Job Family Group: Information Technology Job Description Summary: The Principal Data Engineer is responsible for designing, developing, and optimizing scalable data pipelines, data products, and cloud-based solutions that support business intelligence, advanced analytics, and AI capabilities across the enterprise. This role establishes data engineering standards, promotes best practices, and drives the development of reliable, secure, and high-performing data solutions. As a senior individual contributor, this position provides technical leadership and architectural guidance, collaborates across functional teams, and mentors engineers to support the organization's evolving Data & AI strategy. Job Description: This role follows a flexible hybrid schedule - two days per week in the office and three days working from home. This role can be performed from any Breakthru Beverage office location. Job Responsibilities: Data Pipeline Engineering & Architecture Design, build, and maintain scalable data pipelines on AWS and Snowflake to ingest, transform, and serve enterprise data. Develop ELT/ETL processes using dbt, SQL, and Python to support BI, analytics, and AI use cases. Design curated, scalable, and AI-ready data models and data products for trusted enterprise consumption. Optimize pipelines for performance, scalability, reliability, and cost efficiency. Cloud Data Platform Development Leverage AWS services (S3, Lambda, Glue, DynamoDB, MWAA, etc.) and Snowflake to build secure and resilient data solutions. Implement ingestion frameworks for batch, API, CDC, streaming, and near real-time processing. Design data architectures that support modern AI and machine learning workloads. Ensure proper orchestration, workflow management, and alignment with CI/CD and governance standards. Data Quality, Governance & Observability Embed data quality checks, testing frameworks, and validation controls into pipelines. Support data lineage, metadata management, observability, and AI data governance initiatives. Troubleshoot production data issues and implement sustainable root-cause solutions. Partner with Data Governance to enforce enterprise data standards. Performance, Reliability & Engineering Best Practices Implement CI/CD and Git-based development practices for data pipelines. Monitor, debug, and improve production workflows and platform reliability. Apply software engineering best practices including code reviews, automated testing, and infrastructure-as-code principles. Continuously improve operational excellence and platform scalability. Collaboration & Technical Leadership Partner with BI, Analytics, AI/ML, and business stakeholders to deliver scalable data and AI solutions. Collaborate with AI and Data Science teams to enable model development and AI deployment. Mentor engineers and contribute to architecture standards and engineering best practices. Influence technical direction and communicate complex concepts across technical and business audiences. Minimum Qualifications: Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field. 8 years of experience in Data Engineering, Software Engineering, or related technical roles. Strong expertise in SQL and building scalable, complex data transformations. Proficiency in Python for data engineering, orchestration, and automation workflows. Hands-on experience designing and operating enterprise-grade data platforms on AWS and Snowflake. Experience with dbt or similar modern ELT/transformation frameworks. Proven experience building and optimizing production-grade batch and near real-time data pipelines. Strong understanding of dimensional modeling, curated data layers, and scalable data architecture patterns. Experience designing data solutions that support analytics, AI/ML, and modern AI-driven applications. Expertise with CI/CD, Git-based development workflows, automated testing, and infrastructure-as-code deployments. Strong troubleshooting, problem-solving, and performance optimization skills. Ability to operate effectively in fast-paced, cross-functional enterprise environments. Experience leveraging AI-assisted engineering and developer productivity tools to improve code quality, reliability, and delivery speed. undefined Preferred Qualifications: Experience with data observability and data quality tools. Knowledge of SAP data structures (S/4, BDC data products)Experience in large-scale enterprise environments. This job description is only a summary of the typical functions of this position, not an exhaustive or comprehensive list of all possible job responsibilities, tasks and duties. Responsibilities, tasks, and duties of individual jobholders may vary from the above description. Salary Range: $110,000 - 140,000 Corporate Bonus: 20% - - Breakthru Beverage Group is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information and other legally protected characteristics. The EEO is the Law poster is available here . If you need a reasonable accommodation because of a disability for any part of the employment process, please call (708) 298-3536 and let us know the nature of your request and your contact information.

Requirements

Must-haves

Are you a current Associate? To be considered, you must submit your application through the internal Career Portal (Jobs Hub). Click here to access.
Information Technology
This role follows a flexible hybrid schedule - two days per week in the office and three days working from home.
This role can be performed from any Breakthru Beverage office location.
Data Pipeline Engineering & Architecture
Design, build, and maintain scalable data pipelines on AWS and Snowflake to ingest, transform, and serve enterprise data.
Develop ELT/ETL processes using dbt, SQL, and Python to support BI, analytics, and AI use cases.
Design curated, scalable, and AI-ready data models and data products for trusted enterprise consumption.
Optimize pipelines for performance, scalability, reliability, and cost efficiency.
Cloud Data Platform Development
Leverage AWS services (S3, Lambda, Glue, DynamoDB, MWAA, etc.) and Snowflake to build secure and resilient data solutions.
Implement ingestion frameworks for batch, API, CDC, streaming, and near real-time processing.
Design data architectures that support modern AI and machine learning workloads.
Ensure proper orchestration, workflow management, and alignment with CI/CD and governance standards.
Data Quality, Governance & Observability
Embed data quality checks, testing frameworks, and validation controls into pipelines.
Support data lineage, metadata management, observability, and AI data governance initiatives.
Troubleshoot production data issues and implement sustainable root-cause solutions.
Partner with Data Governance to enforce enterprise data standards.
Performance, Reliability & Engineering Best Practices
Implement CI/CD and Git-based development practices for data pipelines.

Nice-to-haves

Experience with data observability and data quality tools.
Knowledge of SAP data structures (S/4, BDC data products)Experience in large-scale enterprise environments.
Corporate Bonus: 20%

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawssqlpythonapimachine learningci/cdml

Platform: workday
Effort: long