Data Engineer (Python, Data Systems & AI Enablement)

Role OverviewPython-focused Data Engineer with strong hands-on coding skills in data-intensive systems. The role focuses on building scalable data pipelines,processing large datasets, and enabling AI/Generative AI applications through well-structured data infrastructure.Key Responsibilities· Build and maintain scalable data pipelines using Python· Write production-grade Python code specifically for data processing, transformation, and ETL workflows· Perform data cleaning, pre processing, and feature preparation for analytics and AI use cases· Use data analysis and manipulation tools to handle large datasets efficiently· Develop reusable Python modules for data ingestion and pipeline automation· Perform exploratory data analysis (EDA)to understand data patterns and quality issues· Optimize data workflows for performance, scalability, and reliability· Support data requirements for AI/ML and Generative AI systems· Build data services and APIs to support downstream AI applications· Ensure data quality, consistency, and observability across pipelinesRequired Python & Data Libraries (Hands-on Experience Mandatory)Candidates must have strong practical experience with:· pandas — data manipulation, transformation, and analysis· NumPy — numerical operations and array-based processing· Matplotlib — data visualization and reporting· scikit-learn — basic ML workflows and model evaluation· Py Torch — deep learning and AI model experimentationAI /Generative AI Enablement· Prepare and structure datasets for M Land LLM-based systems· Support integration of AI models into data pipelines and applications· Enable workflows for Generative AI use cases (RAG systems, agent workflows)· Work with multiple AI model providers:· OpenAI· Anthropic· LLaMA· Mistral· Exposure to AI orchestration frame works such as Lang Chain, AutoGen, and CrewAICore Requirements· Strong hands-on Python coding expertise focused on data systems (critical requirement)· Ability to write clean, efficient, production-grade Python code· Strong understanding of data structures, ETL pipelines, and data workflows· Experience working with large-scale structured and unstructured data· Strong SQL skills for data extraction and manipulation· Understanding of data modeling and analytics workflows· Ability to support end-to-end data-to-AI pipelinesPreferred /Good to Have· Experience with big data or distributed processing systems· Understanding of vector databases and embedding-based retrieval systems· Experience building APIs or services for data/AI systems· Familiarity with cloud platforms (AWS Azure, GCP)· Exposure to production monitoring and data observability toolsWhat Success Looks Like· High-quality Python code powering scalable data pipelines· Reliable, clean, and well-structured datasets for AI systems· Efficient ETL workflows with minimal manual intervention· Seamless support for ML and GenAI applications in productionR