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# Senior Data Engineer

- **Company:** Akkodis View all jobs
- **Location:** Dearborn, MI, United States
- **Experience:** Expert
- **Salary:** $114,400.0 - $135,200.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Amazon Web Services, Application Performance Management, Microsoft Azure, Big Data, Cloud Computing, Cloud Database, Continuous Delivery, Continuous Integration, Data Architecture, Information Engineering, Extract Transform Load (ETL), DevOps, Apache Hadoop, Python (Programming Language), NoSQL, Cloud Services, Software Engineering, Software Systems, Strategies of Testing, Test-Driven Development (TDD), Sql Optimization, Apache Spark, Kubernetes, Information Technology, Apache Kafka, Data Pipelines, Docker
- **Published:** August 4, 2026
- **Apply:** https://www.careerjet.com/job/usf0797b56a9689410b04eb55740740ab8/eaa

## About the Role

Bachelor's degree in computer science, Software Engineering, Information Technology, Data Engineering, or a related technical field.
5+ years of progressive experience in software engineering, data engineering, or a related role with a strong focus on large-scale data systems.
Expert-level proficiency in Python and/or Java, advanced SQL skills, and hands-on experience with big data technologies such as Apache Spark, Kafka, Hadoop, and NoSQL databases.
Proven experience designing and deploying scalable cloud-based data solutions on AWS, Azure, or GCP, with strong knowledge of data architecture, ETL/ELT processes, Kubernetes, Docker, and cloud infrastructure.

## Description

Rate Range: $55/hour to $65/hour; The rate may be negotiable based on experience, education, geographic location, and other factors.
Senior Data Engineer Job Responsibilities include:
Design, develop, test, and maintain scalable software applications, APIs, and data engineering solutions to support business and customer requirements.
Build and optimize large-scale data pipelines, ETL/ELT processes, and data architectures using technologies such as Python, Spark, Kafka, Hadoop, and cloud-based data services.
Collaborate with product owners, architects, designers, and cross-functional teams to define technical requirements and deliver high-quality software solutions.
Create and implement software testing strategies, leveraging best practices such as test-driven development (TDD), continuous integration (CI), and continuous delivery (CD).
Monitor, troubleshoot, and improve application performance, reliability, scalability, and security, ensuring efficient processing of large data volumes.
Evaluate and adopt emerging technologies, cloud capabilities, and modern engineering practices to enhance development efficiency and support future business needs.


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