Data Engineer

About Company

For the past 80+ years, M&D has led the aftermarket in remanufacturing innovation to address technological advancements and changing customer needs. In the past few decades, we have expanded beyond our remanufacturing roots to develop close (and sometimes exclusive) partnerships with the world’s leading OEMs and manufacturers.

Those partnerships with key suppliers like Bosch, Garrett, Federal Mogul, Cummins, Stanadyne, Holset, BorgWarner, Delphi, Yanmar, Mitsubishi, Denso and others have been critical in honing our remanufacturing capabilities and expanding our parts offering to include new, no core options in fuel injectors and fuel pumps, diesel engine cylinder heads, blocks, crankshafts and connecting rods. M&D also stocks a complete assortment of turbos (new and remanufactured), inframe overhaul kits, filtration and aftertreatment parts including DPFs, DOCs, EGRs, sensors and other engine parts.

Our strong remanufacturing roots combined with our 41 branch locations, a nationwide outside sales team of 25 and our close OEM & Manufacturer partnerships make us unique in the industry – no one understands diesel engine failure analysis and parts better than M&D. WE FUEL UPTIME.

About The Role

As a Data Engineer, you will play a critical role in designing, building, and maintaining scalable data pipelines and architectures that support the organization's data analytics and business intelligence initiatives. You will be responsible for transforming raw data into reliable, accessible, and high-quality datasets that enable data scientists, analysts, and stakeholders to derive actionable insights. This role requires collaboration with cross-functional teams to understand data requirements and implement solutions that optimize data flow and storage. You will also ensure data integrity, security, and compliance with relevant standards while continuously improving data processing performance. Ultimately, your work will empower the organization to make data-driven decisions that drive business growth and innovation.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
• Proven experience in data engineering or a similar role involving large-scale data processing.
• Strong proficiency in SQL and experience with relational databases.
• Hands-on experience with Apache Spark and Hive for big data processing.
• Proficiency in at least one programming language such as Python, Java, or Scala.
• Experience with data ingestion tools like Sqoop and scripting languages for automation.
• Build scalable data architecture for reporting, analytics, and AI initiatives.
• Develop ETL/ELT processes and data quality controls.
• Enable AI and machine learning capabilities with structured data foundations.
• Enable executive dashboards and operational KPI reporting.
• Support predictive analytics, automation, and business intelligence initiatives.
• Optimize database performance, data governance, and master data consistency.
• Partner with departments to create trusted and actionable data models.
• Performs other duties as assigned by supervisor.
  
  

Preferred Qualifications

• Master’s degree in a relevant technical field.
• Experience working in cloud environments such as AWS, Azure, or Google Cloud Platform.
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Knowledge of data warehousing concepts and ETL best practices.
• Experience with real-time data processing frameworks and message queues.
  
  

Responsibilities

• Develop, construct, test, and maintain data architectures such as databases and large-scale processing systems.
• Design and implement data ingestion pipelines using tools like Apache Spark, Hive, and Sqoop to efficiently process structured and unstructured data.
• Write complex SQL queries and optimize them for performance to support data extraction and reporting needs.
• Collaborate with stakeholders to understand data requirements and deliver reliable datasets.
• Monitor and troubleshoot data pipeline issues, ensuring data quality, consistency, and security across systems.
• Automate repetitive data processing tasks using scripting languages and programming languages such as Python, R, Java, and Scala.
• Stay current with emerging data engineering technologies and best practices to continuously enhance data infrastructure.
  
  

Physical Demands and Work Environment

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this position. Reasonable accommodation may be provided to enable individuals with disabilities to perform the functions.

• Prolonged periods sitting at desk and working on a computer
• Ability to lift, move, and carry objects to 15 lbs.
  
  

This job description in no way states or implies that these are the only duties to be performed by the employee(s) of this position. Employees will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments.

M&D provides equal employment opportunity to all qualified applicants and employees without regard to race, color, sex, religion, national origin, age, sexual orientation, gender identity, marital status, familial status, disability, military status, and genetic information.