Job Description: We're looking for an AI Data Engineer to design and build robust data pipelines that power AI/ML and GenAI applications. This role sits at the intersection of traditional data engineering and modern AI infrastructure — you'll be responsible for making data AI-ready, scalable, and production-grade. Key Roles and Responsibilities Design, build, and optimize ETL/ELT pipelines using Python, PySpark, and SQL Develop and maintain scalable data pipelines on Databricks (Delta Lake, notebooks, workflows, cluster optimization) Build data infrastructure to support AI/ML and GenAI use cases — including feature engineering, embeddings, and vector data pipelines Prepare, clean, and structure data (structured & unstructured) for LLM/RAG-based applications Collaborate with Data Scientists and ML Engineers to operationalize models and AI pipelines Ensure data quality, governance, and performance across pipelines Work with cloud platforms (Azure/AWS/GCP) for data storage, compute,
and orchestration Optimize Spark jobs for performance and cost efficiency Required Skills 3–6 years of experience in Data Engineering Strong hands-on expertise in SQL and Python Proficiency in PySpark for large-scale data processing Working experience with Databricks (Delta Lake, Unity Catalog, notebooks) Exposure to AI/ML data pipelines — vector databases, embeddings, or RAG architecture is a plus Experience with cloud data platforms (Azure Data Factory, AWS Glue, or equivalent) Understanding of data modeling, warehousing, and pipeline orchestration (Airflow/ADF) Familiarity with LLM ecosystems (LangChain, LlamaIndex) is an added advantage Good to Have Experience in BFSI or analytics-heavy domains Exposure to MLOps tools and CI/CD for data pipelines Knowledge of NoSQL/vector databases (Pinecone, FAISS, Chroma) What We Offer Opportunity to work on cutting-edge AI/data infrastructure projects Collaborative, fast-paced setting Competitive compensation and growth path into ML/AI architecture role
📌 AI Data Engineer (Haryana)
🏢 EXL
📍 Haryana