Description

Key Responsibilities

Data Pipeline & ETL Engineering: Design, build, and optimize scalable batch/real-time data pipelines across structured and unstructured enterprise SORs using Python, SQL, and cloud integration frameworks.

Process Mining & Task Mining Analytics: Implement process visibility and workflow analytics utilizing Celonis or UiPath Process Mining platforms to pinpoint operational bottlenecks and automation targets.

GenAI & LLM Integration: Customize and deploy enterprise GenAI applications leveraging open-source and proprietary LLMs (Llama, Gemini, OpenAI) for task summarization, process mining insights, and anomaly detection.

Vector Search & RAG Architecture: Build, populate, and query vector databases (Pinecone, FAISS, ChromaDB) to support retrieval-augmented generation and semantic search across enterprise data.

Data Modeling & Analytics Delivery: Construct and maintain data models, warehouses, and real-time executive dashboards to support cross-functional decision-making.

Required Technical Skills & Qualifications

Experience Level: 5+ years of combined experience in Data Engineering, Data Analytics, Machine Learning, or NLP-focused engineering roles.

Process Mining Depth: Direct, hands-on experience using process mining platforms—specifically Celonis or UiPath Process Mining.

Data Engineering Core: Strong proficiency in Python, SQL, data transformation tools, and building cloud-based data pipelines (AWS, Azure, or GCP).

Generative AI & LLM Exposure: Demonstrated work with Generative AI, Large Language Models (LLMs), and vector databases (Pinecone, FAISS).

Data Architecture: Proven track record building and maintaining data models, data lakes, and enterprise data warehouses

Key Skills

Education

Bachelor's degree