Data Engineer I

DHL (Supply Chain)•New Whiteland, IN

47d•Onsite

About The Position

As a Data Engineer I, you’ll design and optimize data pipelines that ensure reliable, accessible information across DHL Supply Chain. You’ll develop and maintain data flows, integrate systems using various tools, and build models that support business objectives. Collaborating with developers, analysts, and data scientists, you’ll implement scalable architectures and identify opportunities to improve data quality and efficiency. This role is perfect for someone ready to enhance data usability and drive impactful solutions in a collaborative environment.

Requirements

Bachelor’s degree in Business, Logistics, Mathematics, Statistics, or a related field, or 4 years of equivalent professional experience, required
1+ years of experience in data engineering or a related technical role, required
Hands on experience developing and managing data pipelines, required
Strong understanding of SQL and experience with database management systems such as MySQL, PostgreSQL, or SQL Server, required
Proficiency in programming languages such as Python, Java, or Scala, required
Familiarity with data warehousing solutions and working with large datasets, required
Knowledge of data modeling, ETL processes, and data warehousing concepts—particularly within Azure environments, required

Nice To Haves

Experience with Azure Data Factory, Azure Databricks, or Azure Synapse Analytics, preferred
Ability to work with data visualization tools such as Power BI, preferred
Understanding of data governance and data quality principles, preferred

Responsibilities

Support developers, architects, analysts, and data scientists by improving data accessibility and usability.
Maintain consistency across projects by following established data delivery architecture standards.
Recommend and implement data pipeline designs that optimize data flow for cross functional teams.
Design, build, and deploy data processes that serve multiple systems and products.
Develop and sustain data workflows for modeling, mining, and production, identifying opportunities for new data acquisition and integration.
Use a variety of languages and tools to integrate systems and enhance data reliability, efficiency, and quality.
Architect, build, and launch data models that support business objectives and strengthen analytics capabilities.
Collaborate with cross functional partners to ensure data initiatives align with organizational goals and stakeholder needs.