Python / PySpark Engineer with AI Experience

Python/PySpark Engineer

Key Responsibilities

• Develop and optimize data pipelines using

  Python

  and

  PySpark

  .
• Work with large-scale datasets in distributed computing environments.
• Collaborate with data scientists to prepare, transform, and operationalize data for ML models.
• Implement and maintain data quality, validation, and monitoring frameworks.
• Support ML model deployment, performance tracking, and lifecycle management.
• Apply AI/ML concepts such as feature engineering, model evaluation, and inference workflows.
• Integrate data from cloud storage, APIs, databases, and streaming sources.
• Follow best practices for code quality, version control, and CI/CD automation.

Required Skills & Experience

• 3+ years of hands-on experience with

  Python

  for data engineering or data-related development.
• Strong experience with

  PySpark

  and distributed data processing.
• Understanding of

  AI/ML concepts

  (feature engineering, training pipelines, model monitoring, etc.).
• Experience with cloud platforms (Azure / AWS / GCP).
• Strong SQL skills for data manipulation and performance tuning.
• Experience with Git and CI/CD pipelines.
• Ability to work in a fast-paced, collaborative environment.

Preferred Qualifications

• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Exposure to MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML).
• Experience with orchestration tools such as Airflow, ADF, or Databricks Workflows.
• Familiarity with data-lake and lakehouse architectures.
• Knowledge of data visualization tools (Power BI, Tableau).

What We Offer

• Competitive salary and benefits package.
• Opportunity to work with modern data and AI technologies.
• Learning and certification support.
• Collaborative and innovative work environment.