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# Full Stack Data Engineer

- **Company:** Artech
- **Location:** Dearborn, MI, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Business Analytics Applications, Data Analysis, BigQuery, Cloud Computing, Cloud Database, Information Systems, Databases, Information Engineering, Data Governance, Data Infrastructure, Data Masking, Data Warehousing, Relational Databases, Data Flow Control, Python (Programming Language), PostgreSQL, MySQL, NoSQL, Systems Development Life Cycle, Cloudera, Service-Oriented Architecture, Software Engineering, SQL Databases, Unstructured Data, Enterprise Data Management, Scripting, Google Cloud, Cloud Platform System, Data Lakes, Infrastructure Automation Frameworks, Information Technology, Google Cloud Functions, Data Analytics, Data Management, Data Lakehouse, Terraform, Data Pipelines, Microservices
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/full-stack-data-engineer-dearborn-mi--bed94bb7-a3ef-4b15-8cac-cd94cd4d2165

## About the Role

Data Management, Cloud Computing, Best Practices, GCP (Good Clinical Practices), Scalable System Development, Computer Science, Data Analysis, Information Technology & Information Systems, Software Engineering, Java, * Bachelor's degree in Computer Science, Information Technology, Information Systems, Data Analytics, or a related field (or equivalent combination of education and experience).

 * 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.
 * Passion for data, innovation, and continuous learning.
 * Applicants must be able to work directly for Artech on W2, * Master's Degree
 * Experience in monitoring and optimizing cost and compute resources for processes in GCP technologies (e.g., BigQuery, Dataflow, Cloud Run, DataProc).
 * Prior work experience in the industry.

## Description

We're seeking a highly skilled and experienced professional 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. This is a fantastic opportunity to leverage your full-stack expertise, collaborate with talented teams, and establish best practices for data engineering., * Collaborate with business and technology stakeholders to understand current and future data requirements.

 * Design, build, and maintain reliable, efficient, and scalable data infrastructure for data collection, storage, transformation, and analysis.
 * Plan, design, build, and maintain scalable data solutions including data pipelines, data models, and applications for efficient and reliable data workflow.
 * Design, implement, and maintain existing and future data platforms like data warehouses, data lakes, data lakehouse, etc., for structured and unstructured data.
 * Design and develop analytical tools, algorithms, and programs to support data engineering activities like writing scripts and automating tasks.
 * Ensure optimum performance and identify improvement opportunities.