Principal Data Engineer

Breakthru Beverage Group

. Design, build, and maintain scalable data pipelines on AWS and Snowflake to ingest, transform, and serve enterprise data .

Posted 10/16/2026full-timeUnited StatesLead💰 $110,000 - $140,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines using AWS and Snowflake, with a strong focus on ELT/ETL processes, data architecture, and AI readiness. Proficient in SQL and Python, with a solid understanding of CI/CD practices and data governance standards.

Highest-signal resume keywords

AWS Data Pipeline DevelopmentSQL Data TransformationPython Automation WorkflowsCI/CD ImplementationData Architecture Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonDbtData Pipeline OptimizationData ModelingETL ProcessesData GovernanceInfrastructure-as-CodeAutomated TestingPerformance Optimization

Soft Skills

Problem-SolvingCollaborationMentoringCommunicationTroubleshooting

Tools & Technologies

AWS S3AWS LambdaAWS GlueAWS DynamoDBSnowflakeGitMWAAData Quality ToolsData Observability ToolsAI/ML Frameworks

Industry Keywords

Data EngineeringEnterprise Data StandardsAI-Driven ApplicationsCross-Functional CollaborationLarge-Scale Enterprise Environments

Tech Stack

Tools & technologies

AWSDynamoDBETLPythonSQL

About the role

Key responsibilities & impact

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 for BI, analytics, and AI use cases
Design curated, scalable, and AI-ready data models and data products
Optimize pipelines for performance, scalability, reliability, and cost efficiency
Leverage AWS services including S3, Lambda, Glue, DynamoDB, and MWAA, along with Snowflake
Implement ingestion frameworks for batch, API, CDC, streaming, and near real-time processing
Design data architectures supporting modern AI and machine learning workloads
Ensure orchestration, workflow management, CI/CD alignment, and governance standards
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
Implement CI/CD and Git-based development practices for data pipelines
Monitor, debug, and improve production workflows and platform reliability
Apply code reviews, automated testing, and infrastructure-as-code principles
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

Requirements

What you’ll need

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

Benefits

Comp & perks

Flexible hybrid schedule with two days per week in the office and three days working from home
Corporate Bonus: 20%