AI/ML Data Engineer (Pytest and PySpark, Databricks)

About Company, Droisys is an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies, and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction. Amazing things happen when we work in environments where everyone feels a true sense of belonging and when candidates have the requisite skills and opportunities to succeed. At Droisys, we invest in our talent and support career growth, and we are always on the lookout for amazing talent who can contribute to our growth by delivering top results for our clients. Join us to challenge yourself and accomplish work that matters. Here's the job details, AI/ML Data Engineer (Pytest and PySpark, Databricks) Plano, TX (Onsite) Interview Mode: Video + In-Person Rate Range $40 to $46 hr W2 All Inc Job Description: We are seeking an experienced Data Engineer with a strong background in PySpark, Databricks, AI/ML integration, and automated testing using Pytest. The ideal candidate will design, develop, and optimize scalable data pipelines, ensuring reliability and performance across analytical and machine learning workloads. This role requires hands-on technical expertise, strong analytical thinking, and a collaborative mindset. Responsibilities: • Design, develop, and maintain scalable data pipelines using PySpark and Databricks. • Integrate AI/ML models into existing data workflows for predictive analytics and intelligent automation. • Implement robust testing frameworks using Pytest to validate data quality, transformations, and pipeline integrity. • Optimize data storage and processing performance across distributed systems. • Collaborate with data scientists, AI engineers, and business analysts to enable machine learning workflows. • Develop CI/CD processes for data pipelines and model deployment within Databricks. • Troubleshoot and resolve performance issues across large-scale datasets. • Document and maintain best practices for coding, testing, and deployment. Required Skills: • Strong experience with PySpark for large-scale data transformation and ETL. • Hands-on expertise in Databricks environment (cluster management, job orchestration, and notebooks). • Proficient in Pytest for unit testing and data validation automation. • Experience in AI/ML pipelines — model training, evaluation, and integration with data engineering workflows. • Strong programming skills in Python and SQL. • Knowledge of Delta Lake, Azure Data Lake, or AWS S3 environments. • Familiarity with CI/CD tools (Git, Jenkins, Azure DevOps). • Excellent analytical and problem-solving skills. Preferred Qualifications: • Experience with MLflow or MLOps frameworks. • Exposure to cloud-based data ecosystems (Azure, AWS, or GCP). • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field Droisys is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Droisys believes in diversity, inclusion, and belonging, and we are committed to fostering a diverse work environment.