DATA ENGINEER I

 

                                                                              Data Engineer I

Who We Are

US Cold owns and operates one of the most complex temperature-controlled logistics networks in North America. Every day, our systems coordinate the storage and movement of food at national scale across a network of state-of-the-art distribution centers, including multiple highly automated warehouse facilities

As US Cold continues to modernize its technology landscape, data has become a critical asset driving operational excellence, business intelligence, automation, and AI-enabled decision making across the organization. Our Data Engineering team builds and supports trusted, scalable, and secure data platforms that power analytics, reporting, forecasting, and machine learning solutions across the enterprise

If you are passionate about building modern data solutions, learning emerging technologies, and helping transform data into business value, this is that opportunity

The Role

The Data Engineer I helps design, build, and support the data platforms and pipelines that power analytics, reporting, operational insights, and AI-driven solutions at US Cold Storage. You will work closely with Data Engineers, Data Scientists, Analytics Engineers, and business stakeholders to ensure reliable, high-quality data is available for decision-making across the organization

This role is ideal for an early-career data professional with strong SQL and Python fundamentals who is eager to learn modern cloud data platforms, data engineering practices, and production-scale data operations.

What You Will Own

• Design, build, test, and maintain batch and streaming data pipelines
• Develop and support data ingestion processes from databases, APIs, files, logs, and other enterprise systems
• Write clean, maintainable SQL and Python code to support data transformation and pipeline orchestration
• Monitor and improve data quality, reliability, freshness, and observability across assigned datasets
• Support analytics, reporting, and data science initiatives through the delivery of trusted data assets
• Apply best practices in data modeling, testing, source control, documentation, and deployment
• Participate in agile ceremonies, code reviews, and technical design discussions
• Troubleshoot pipeline failures and support root-cause analysis efforts
• Contribute to automation and continuous improvement initiatives across the data platform
• Collaborate with business and technical teams to understand data requirements and deliver scalable solutions
• Support production data environments and participate in operational support activities when required
• Stay current on modern data engineering, cloud technologies, analytics platforms, and AI-enabled data workflows

Technical Environment

• SQL and Python
• Batch and Streaming Data Pipelines
• ETL and ELT Frameworks
• Snowflake, Azure Synapse, BigQuery, Redshift, or Similar Cloud Data Warehouses
• Azure, AWS, or GCP Cloud Platforms
• Data Modeling and Data Quality Frameworks
• Git and Source Control Platforms
• Power BI and Tableau
• AI, Machine Learning, and LLM-Enabled Data

What We're Looking For

• 1-2 years of professional experience in Data Engineering or a related technical field
• Strong SQL skills including joins, aggregations, window functions, and query optimization
• Experience developing solutions using Python or similar programming languages
• Understanding of data pipelines, ETL/ELT processes, data modeling, and modern data architectures
• Familiarity with cloud platforms such as Azure, AWS, or GCP
• Strong analytical, troubleshooting, and problem-solving skills
• Ability to communicate effectively with both technical and business stakeholders
• Demonstrated curiosity, adaptability, and desire to learn emerging technologies
• Bachelor's or Master's degree in Computer Science, Data Engineering, Mathematics, Information Systems, Engineering, or a related discipline, or equivalent experience

Preferred Qualifications

• Experience with Snowflake, Azure Synapse, BigQuery, Redshift, or similar cloud data platforms
• Exposure to AI, prompt engineering, LLM pipelines, or advanced analytics solutions
• Understanding of data governance, privacy, security, and access management principles
• Experience with business intelligence and visualization tools such as Power BI or Tableau
• Participation in open-source projects, hackathons, academic research, or technical portfolio work
• Exposure to e