Data Engineer

Position: Data EngineerLocation: Dearborn, MI - hybrid 2x a week onsitePay: $72-78hrType: W2, FTSummary: The primary focus of this role is the development and maintenance of applications that ingest data from multiple engineering systems on the backend. These applications will feature an AIML-enabled web front end to provide predictive analytics, automation, and engineering insights.Responsibilities:Collaboration: Work closely with data scientists, product managers, and other developers to conceptualize and execute on project requirements. Testing and Deployment: Write unit and integration tests, manage CICD pipelines, and ensure smooth deployments to production environments. Documentation: Maintain clear documentation for systems, services, and models to support future maintenance and development.Skills Required:Database Management:Work with databases for data storage, retrieval, and management tailored to AIML needs.Strong experience with ETL processes (e.g., using tools like Apache Kafka, Talend, or custom scripts).Knowledge of various database systems (SQL, NoSQL like MongoDB, Cassandra).Experience with data warehousing concepts and tools (e.g. Google BigQuery).AIML Integration: Incorporate machine learning models into our applications to enhance functionality, including but not limited to natural language processing, image recognition, and predictive analytics.Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn for model development. Knowledge of chatbot development platforms like Dialogflow.Knowledge of frameworks like LangChain and Retrieval Augmented Generation (RAG).Full Stack Development: Design, develop, and maintain scalable and efficient web applications using modern frameworks (e.g., React, Angular for frontend; Node.js, Django for backend).Cloud Services: Proficiency in at least one major cloud platform (Google Cloud preferred) for data storage, processing, and hosting AI services.API Development: Develop RESTful APIs to ensure seamless integration between frontend, backend, and external services. DevOps: Basic understanding of CICD pipelines, containerization (Docker), and orchestration (Kubernetes).Performance Optimization: Continuously improve application performance through code refactoring, optimization of data pipelines, and tuning of machine learning models.Experience Required:• At least 5 years of experience in Data Engineering with a focus on full stack development. • Proven experience in developing applications with integrated AIML features.Education Required:• Bachelorsmaster's degree in computer science, Information Technology, or related fields with a special focus on Data Engineering and AIML.Education Preferred:• Certifications in AIML like Google's Professional Machine Learning Engineer are optional but beneficial.

Created: 2025-02-22