Data Engineer III+ (Analytics Focus)

Company Description

“We’re not in the shipping business; we’re in the information business” -Peter Rose, Expeditors Founder

Global supply chain management is what we do, but at the heart of Expeditors you will find professionalism, leadership, and a friendly environment, all of which foster an innovative, customer service-based approach to logistics.

• 15,000 trained professionals
• 250+ locations worldwide
• Fortune 500
• Globally unified systems

Job Description

As a Data Engineer (Analytics Focus), you will bridge the gap between data engineering and data analysis by building robust data models and pipelines that support analytics and reporting. You will work closely with data engineers, analysts, and business stakeholders to ensure data accuracy, performance, and accessibility within our data infrastructure. 

This position is within the GEO-IS Data Platforms Product Development team, supporting our GEO-IS Solutions data infrastructure. Currently, our data pipelines and infrastructure are on-premises, but we will be migrating to the cloud later this year. As part of this role, you will help design, optimize, and transition data pipelines to the cloud, in addition to creating new data pipelines with a focus on creating scalable and efficient data models. 

Additionally, we are looking for someone with experience in Power BI performance optimization and integrating Power BI with Azure-based data solutions. The ideal candidate will help ensure efficient data processing, optimal report performance, and seamless integration between our data infrastructure and Power BI. 

A successful Data Engineer III should excel at the following: 

1. Demonstrates a strong problem-solving mindset with a focus on optimizing data processes. 

1. Effectively communicates technical concepts to non-technical stakeholders. 

1. Proactively collaborates with cross-functional teams to ensure data accuracy and accessibility. 

1. Continuously learns and adapts to emerging data technologies and best practices. 

Major Duties and Responsibilities 

• Design and develop data models to support BI and analytics, focusing on performance and scalability. 

• Build and maintain data pipelines that transform raw data into clean, usable data sets. 

• Perform data transformations using SQL and scripting languages (e.g., Python). 

• Collaborate with data engineers to ensure data availability and integrity. 

• Validate data outputs for accuracy and consistency through rigorous testing. 

• Implement data quality checks and maintain data documentation. 

• Work with stakeholders to define metrics, KPIs, and reporting needs. 

• Support the migration of on-prem solutions to the cloud. 

• Support BI tools (e.g., Power BI) by building efficient data models that enhance performance. 

• Participate in code reviews and contribute to team best practices such as documenting data models and processes, and enforcing data governance and security 

• Monitor pipeline performance and address data inconsistencies and bottlenecks. 

• Collaborate with the team to optimize database performance and storage solutions. 

Qualifications

Minimum

• Bachelor's degree in an IT-related field or equivalent experience. 

• 3-5 years of experience in data transformation, data modeling, and analytics engineering. 

• Strong experience with SQL and query optimization across multiple databases. 

• Proficiency in Python for data processing and automation. 

• Experience with Airflow or other workflow orchestration tools. 

• Experience with Azure cloud-based data solutions. 

• Hands-on experience with ETL/ELT frameworks and workflow automation tools. 

• Strong understanding of data modeling and schema design for analytics and reporting. 

• Hands-on experience migrating on-prem data pipelines to the cloud, including strategy, execution, and optimization. 

• Experience with Power BI performance optimization and integrating Power BI with Azure. 

• Demonstrated ability to collaborate with cross-functional teams and stakeholders. 

Desired 

• Experience with Azure Fabric, Azure Synapse, or Databricks. 

• Familiarity with infrastructure-as-code (Terraform, ARM templates). 

• Experience with data tra