Position: Full-Stack Data Engineer
Location: Dearborn, MI (Hybrid)
Employment Type: Full-Time Contract
Pay: $56-59 per hour
Description: We’re seeking a highly skilled and experienced Full Stack Data Engineer to play a pivotal role in the development and maintenance of our Enterprise Data Platform. In this role, you’ll be responsible for designing, building, and optimizing scalable data pipelines within our Google Cloud Platform (GCP) environment. You’ll work with GCP Native technologies like BigQuery, Dataflow, and Pub/Sub, ensuring data governance, security, and optimal performance.
Responsibilities:
- Design, develop, and maintain scalable enterprise data pipelines using GCP technologies including BigQuery, Dataflow, Pub/Sub, and DataProc.
- Build and optimize cloud-native data solutions to support enterprise analytics and business intelligence initiatives.
- Implement data governance, security, encryption, and data masking solutions to ensure compliance and data integrity.
- Develop and support microservices and Service-Oriented Architecture (SOA) components within the enterprise data platform.
- Monitor and optimize platform performance, compute usage, and cloud costs across GCP services.
- Collaborate with cross-functional teams including data engineers, software developers, architects, and business stakeholders.
- Design and implement CI/CD pipelines and Infrastructure as Code (IaC) solutions using tools such as Terraform and Tekton.
- Troubleshoot and resolve complex platform, pipeline, and microservices issues.
- Establish and promote best practices for cloud-based data engineering, automation, and platform reliability.
- Continuously evaluate emerging technologies and drive innovation within the data engineering ecosystem.
Requirements:
- Bachelor’s degree in Computer Science, Information Technology, Information Systems, Data Analytics, or a related field
- 5-7 years of experience in Data Engineering or Software Engineering, with at least 2 years of hands-on experience building and deploying cloud-based data platforms (GCP preferred).
- Strong proficiency in SQL, Java, and Python, with practical experience in designing and deploying cloud-based data pipelines using GCP services like BigQuery, Dataflow, and DataProc.
- Solid understanding of Service-Oriented Architecture (SOA) and microservices, and their application within a cloud data platform.
- Experience with relational databases (e.g., PostgreSQL, MySQL), NoSQL databases, and columnar databases (e.g., BigQuery).
- Knowledge of data governance frameworks, data encryption, and data masking techniques in cloud environments.
- Familiarity with CI/CD pipelines, Infrastructure as Code (IaC) tools like Terraform and Tekton, and other automation frameworks.
- Excellent analytical and problem-solving skills, with the ability to troubleshoot complex data platform and microservices issues.
- Experience in monitoring and optimizing cost and compute resources for processes in GCP technologies (e.g., BigQuery, Dataflow, Cloud Run, DataProc).
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