Data Engineer III/Senior (Analytics)

Expeditors•Romulus, MI

14h•$130,000 - $170,000•Onsite

About The Position

We are seeking a highly skilled and hands-on Data Engineer III or Senior Data Engineer (Analytics Focus) to design, build, and support enterprise analytics solutions, data models, and reporting experiences that enable data-driven decision making across the organization. This is first and foremost an analytics-focused data engineering role. The ideal candidate has strong expertise in data modeling, analytics engineering, Microsoft Fabric, Databricks, Python development, and modern business intelligence solutions. The successful candidate will be responsible for developing and maintaining enterprise data models, semantic layers, reporting datasets, and analytical applications that support operational reporting, executive dashboards, self-service analytics, and advanced business insights. This role sits within the engineering discipline and works closely with product teams, platform engineers, architects, and business stakeholders to ensure enterprise reporting and analytics solutions are built on reliable data foundations, aligned with business objectives, and capable of scaling with future needs. This position supports the Americas geography under the IS organization and contributes to initiatives that enhance operations across 70+ offices in multiple countries.

Requirements

Bachelor’s degree with 5+ years, or Master’s with 3+ years, or equivalent experience (for Data Engineer III)
Bachelor’s degree with 10+ years, Master’s with 5+ years, or PhD with 3+ years (for Senior Data Engineer)
Advanced proficiency in designing, developing, and optimizing enterprise data models and semantic layers that support scalable analytics.
Demonstrated expertise in developing scalable reporting and analytics solutions using enterprise visualization tools.
Knowledge of data governance, data privacy regulations (e.g., GDPR, CCPA), and best practices for ensuring data security and compliance.
Expert-level proficiency in writing, optimizing, and troubleshooting complex SQL queries across multiple databases
Proven expertise designing and implementing end-to-end analytics solutions using Microsoft Fabric and Databricks, including data modeling, semantic layer development, performance optimization, and analytics architecture.
Expert proficiency in data visualization applications, including Power BI, Tableau, and Python visualization libraries (e.g., Matplotlib, Seaborn, Plotly).
Experience implementing Git-integrated CI/CD frameworks for Microsoft Fabric, Databricks, and analytics platforms, including automated validation, deployment pipelines, release governance, and measurement of engineering performance through DORA metrics.
Applicants are required to be eligible to lawfully work in the U.S. immediately; employer will not transfer or sponsor applicants for U.S. work authorization (such as an H-1B visa) for this opportunity.

Nice To Haves

Relevant certifications in Analytics and Cloud platforms (Databricks Data Engineer Professional, Power BI Data Analyst, Azure Solutions Architect Expert)

Responsibilities

Building enterprise analytics solutions using Microsoft Fabric, Databricks, SQL, Python, and Power BI.
Design and develop semantic models and reporting datasets that support self-service analytics and executive reporting.
Creating intuitive, user-focused reporting experiences that improve data visibility and decision making.
Translating complex business requirements into scalable analytical solutions.
Establishing data quality standards and validation processes that ensure trust in reporting.
Optimizing analytics solutions for performance, usability, and maintainability.
Leading data design discussions and influencing data architecture and modeling best practices.
Collaborating effectively with business stakeholders to define KPIs, metrics, and reporting requirements.
Mentoring team members and promoting engineering excellence through collaboration, design reviews, and knowledge sharing.
Lead the development of enterprise data models, semantic layers, analytics solutions, and reporting datasets that provide trusted and scalable business insights.
Establish and promote best practices for data quality, testing, automation, observability, version control, CI/CD and operational excellence across analytics solutions.
Provide technical leadership through code reviews, solution design guidance, and mentorship of engineers on performance, maintainability, scalability, and solution quality.
Design scalable data models, reporting architecture, and analytics solutions that support current and future business needs.
Partner with architects and engineering leaders to ensure solutions align with enterprise engineering principles and standards for metric governance, semantic modeling, and analytics solutions.
Evaluates scale on solution footprint
Collaborate with engineering, architecture, product, and business teams to deliver high-impact analytics capabilities.
Serve as a trusted technical partner in translating business requirements into actionable data and reporting solutions.
Mentor team members through coaching, knowledge sharing, and constructive technical feedback.
Advocate for analytics engineering best practices, standardized metrics, and data-driven decision making across teams and department.
Communicate technical concepts, data insights, and solution recommendations to both technical and non-technical audiences.
Influence reporting, data modeling, and analytics strategies through active participation in architectural and business discussions.
Develop and communicate a strategic vision for analytics, reporting, and data visibility solutions aligned to business priorities.
Identify opportunities to improve organizational visibility, operational performance, and analytical capabilities by balancing immediate delivery needs with long-term sustainability, scalability, and maintainability of analytics solutions.
Develop a deep domain knowledge of logistic operations, understanding business processes and key performance metrics to guide solution design.
Ensure analytics solutions deliver actionable insights that support measurable business outcomes and operational improvements.
Continuously improve the usability, accessibility, and effectiveness of data products, reports, and analytical experiences for end users.