Data Engineer C2C requirements
Sr. Data Engineer (Python, Pyspark, Airflow, SDET)
Auburn Hills, MI
12+ Months Contract
Job Description:
The Senior Data Engineer & Technical Lead (SDET Lead) will play a pivotal role in delivering major data engineering initiatives within the Data & Advanced Analytics space. This position requires hands-on expertise in building, deploying, and maintaining robust data pipelines using Python, PySpark, and Airflow, as well as designing and implementing CI/CD processes for data engineering projects
Mandatory Skills: Data Engineering, Python, PySpark, CI/CD, Airflow, Workflow Orchestration
Key Responsibilities:
Data 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.
Cross-Team Knowledge Sharing: Cross-train team members outside the project team (e.g., operations support) for full knowledge coverage. Includes all above skills, plus the following.
Minimum of 7+ years overall IT experience
Experienced in waterfall, iterative, and agile methodologies
Technical Experience:
Hands-on Data Engineering: Minimum 5+ yearsof 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.
Unique Skills:
Graduate degree in a related field, such as Computer Science or Data Analytics
Familiarity with Test-Driven Development (TDD)
A high tolerance for OpenShift, Cloudera, Tableau, Confluence, Jira, and other enterprise tools.
To apply for this job email your details to arjun@centraprise.com