Bus. Proc. & Strat. Senior Analyst

Job description

Job Summary We are looking for an Associate Data AI Engineer (G9) with a solid foundation in data engineering on Azure and growing experience in Generative AI technologies such as RAG and LLM-based solutions. This is an individual contributor role suited for a candidate who is eager to expand their expertise across data engineering and AI, working on modern data platforms and emerging AI use cases. The ideal candidate is hands-on, curious, and adaptable, with the ability to contribute to both data pipeline development and AI-driven solutions. Key Responsibilities Data Engineering • Support the design and development of data pipelines using Azure Data Factory, Databricks, and related services. • Develop and maintain data transformations and workflows using SQL and PySpark. • Work with structured and unstructured data to support analytics and AI use cases. • Assist in implementing data models and optimizing data processing performance. GenAI AI Development • Contribute to building Generative AI solutions using LLMs (e.g., Azure OpenAI, OpenAI). • Assist in developing RAG pipelines (data ingestion, embeddings, retrieval). • Support implementation of basic Agentic AI workflows using frameworks like LangChain or similar. • Participate in prompt engineering and testing of AI applications. Databricks Processing • Use Azure Databricks for data processing and transformation tasks. • Develop and maintain PySpark-based pipelines under guidance from senior team members. Python Machine Learning • Write Python code for data processing, automation, and basic ML workflows. • Assist in data preparation, feature engineering, and model evaluation. Collaboration Learning • Work closely with senior engineers, architects, and stakeholders on project delivery. • Actively learn and adopt new technologies in Azure and Generative AI. • Contribute to documentation and knowledge sharing within the team. Required Skills Experience Mandatory • 35 years of experience in data engineering, software engineering, or AI/ML roles. • Hands-on experience with Python. • Working knowledge of SQL and data handling. • Exposure to Microsoft Azure (Data Factory, storage, or compute services). • Basic experience with Azure Databricks or PySpark. • Exposure to Generative AI concepts, such as: • LLMs and prompt engineering • Basic understanding of RAG workflows • Experience with data pipelines (ETL/ELT) concepts. Nice to Have • Hands-on experience with Azure OpenAI or similar LLM APIs. • Basic understanding of machine learning concepts and libraries. • Experience with Power BI or data visualization tools. ",