Data Engineer

Packsize•Salt Lake City, UT

12d•Hybrid

About The Position

Packsize is redefining the way businesses and their customers use and experience packaging around the world. We build the technology, design the right solutions, and automate the processes that propel the industry forward. To us, packaging is much more than a box—it’s delivering what’s right for our customers, their customers, our people, and the planet. We are seeking a Data Engineer to design, build, and optimize data pipelines and architectures that empower data-driven decision-making and business growth. In this hands-on technical role, you will collaborate with cross-functional teams to gather requirements, architect scalable data solutions, and implement best-in-class data engineering practices. You will play a key role in advancing our data analytics capabilities, ensuring data is reliable, accessible, and aligned with business objectives.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent professional experience in data engineering or related technical roles.
7+ years of experience in data engineering and analytics or data integration.
Expertise in modern data analytics, including building and optimizing data pipelines for near-real-time and batch processing.
Proven skills in data architecture, with a focus on designing scalable and efficient data systems.
Advanced proficiency in SQL for complex querying, optimization, and data transformation.
Intermediate proficiency in Python for scripting, automation, and ETL development.
Advanced dimensional modeling skills, with experience designing star schemas and semantic layers for analytics.
Expertise in building metadata driven pipelines, integrations, and methods for improving maintainability and reducing technical debt.
Experience in semantic layer design to support business intelligence tools and self-service analytics.
Strong collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders.
Ability to gather requirements and translate them into technical solutions that align with business goals.
Self-driven and motivated, with a track record of delivering high-impact results and moving the needle for business value.
Experience with modern data platforms (e.g., DOMO, Databricks, Snowflake, Fabric) and tools.

Nice To Haves

Knowledge of data governance, data quality, and data integration best practices is a plus.
Professional certifications (e.g., Azure Data Engineer, AWS Certified Data Engineer, Google Cloud Professional Data Engineer) are a plus.

Responsibilities

Design, develop, and maintain scalable data pipelines and architectures to support modern data analytics and integration needs.
Build and optimize data models, including advanced dimensional modeling and semantic layer design, to enable efficient querying and reporting.
Implement robust ETL/ELT processes using intermediate Python and advanced SQL to ensure high-quality data delivery.
Collaborate with business units, analysts, and stakeholders to gather requirements and translate them into technical solutions that drive measurable business value.
Ensure best-in-class implementation of data engineering solutions, focusing on performance, scalability, and maintainability.
Contribute to the development and maintenance of data warehouses, data lakes, and integration pipelines.
Proactively identify and resolve data quality issues, ensuring data integrity and consistency across systems.
Work closely with data analysts and other engineers to support data-driven initiatives and deliver actionable insights.
Stay current with industry trends and emerging tools to continuously improve data engineering practices.
Document technical designs, processes, and solutions to support team collaboration and knowledge sharing.