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 ResponsibilitiesDesign, build, and optimize ETL/ELT pipelines using Python, PySpark, and SQLDevelop 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 pipelinesPrepare, clean, and structure data (structured & unstructured) for LLM/RAG-based applicationsCollaborate with Data Scientists and ML Engineers to operationalize models and AI pipelinesEnsure data quality, governance, and performance across pipelinesWork with cloud platforms (Azure/AWS/GCP) for data storage, compute,



and orchestrationOptimize Spark jobs for performance and cost efficiencyRequired Skills3–6 years of experience in Data EngineeringStrong hands-on expertise in SQL and PythonProficiency in PySpark for large-scale data processingWorking experience with Databricks (Delta Lake, Unity Catalog, notebooks)Exposure to AI/ML data pipelines — vector databases, embeddings, or RAG architecture is a plusExperience 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 advantageGood to HaveExperience in BFSI or analytics-heavy domainsExposure to MLOps tools and CI/CD for data pipelinesKnowledge of NoSQL/vector databases (Pinecone, FAISS, Chroma)What We OfferOpportunity to work on cutting-edge AI/data infrastructure projectsCollaborative, quick-paced environmentCompetitive compensation and growth path into ML/AI architecture role

📌 AI Data Engineer (Mumbai)
🏢 EXL
📍 Mumbai