Python Technical Architect/ Lead

Sr Python DeveloperLocation: Auburn Hills, MI- OnsiteMandatory Skills: Data Engineering, Python, PySpark, CI/CD, Airflow, Workflow OrchestrationKey ResponsibilitiesData Engineering: Design, develop, and optimize scalable data pipelines using Python and PySpark for batch and streaming workloads.Workflow Orchestration: Build, schedule, and monitor complex workflows using Airflow, ensuring reliability and maintainability.CI/CD Pipeline Development: Architect and implement CI/CD pipelines for data engineering projects using GitHub, Docker, and cloud-native solutions.Testing & Quality: Apply test-driven development (TDD) practices and automate unit/integration tests for data pipelines.Secure Development: Implement secure coding best practices and design patterns throughout the development lifecycle.Collaboration: Work closely with Data Architects, QA teams, and business stakeholders to translate requirements into technical solutions.Documentation: Create and maintain technical documentation, including process/data flow diagrams and system design artifacts.Mentorship: Lead and mentor junior engineers, providing guidance on coding, testing, and deployment best practices.Troubleshooting: Analyze and resolve technical issues across the data stack, including pipeline failures and performance bottlenecks.Technical ExperienceHands-on Data Engineering: Minimum 5+ years of practical experience building production-grade data pipelines using Python and PySpark.Airflow Expertise: Proven track record of designing, deploying, and managing Airflow DAGs in enterprise environments.CI/CD for Data Projects: Ability to build and maintain CI/CD pipelines for data engineering workflows, including automated testing and deployment.Cloud & Containers: Experience with containerization (Docker and cloud platforms (GCP) for data engineering workloads. Appreciation for twelve-factor design principles.Python Fluency: Ability to write object-oriented Python code manage dependencies, and follow industry best practices.Version Control: Proficiency with Git for source code management and collaboration (commits, branching, merging, GitHub/GitLab workflows).Unix/Linux: Strong command-line skills in Unix-like environments.SQL: Solid understanding of SQL for data ingestion and analysis.Collaborative Development: Comfortable with code reviews, pair programming and using remote collaboration tools effectively.Engineering Mindset: Writes code with an eye for maintainability and testability; excited to build production-grade software.Education: Bachelor's or graduate degree in Computer Science, Data Analytics or related field, or equivalent work experience.A high tolerance for OpenShift, Cloudera, Tableau, Confluence, Jira, and other enterprise tools.