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Core Data Science - strong foundation in statistics, probability, ML/DL algorithms, and model evaluation techniques Python & SQL - solid proficiency; you think in Python and speak fluent SQL ML Toolkit - hands-on experience with Pandas, NumPy, Scikit-learn, and at least one deep learning framework (PyTorch / TensorFlow) Generative AI & LLMs - working knowledge of large language models (GPT, LLaMA, etc.), prompt engineering, and prompt optimization techniques RAG & Embeddings - understanding of Retrieval-Augmented Generation architectures, vector databases (FAISS, Pinecone, Weaviate), and embedding strategies LLM Frameworks - exposure to LangChain, LangGraph, or similar orchestration frameworks Communication - ability to distill complex analysis into clear insights for both technical and non-technical audiences Mindset - strong problem-solving instincts, intellectual curiosity, and a bias for action.

The Junior Data Engineer will support day-to-day monitoring, first-level checks, basic troubleshooting, data validation, ticket updates, and documentation activities for data engineering pipelines and applications. This role requires a basic understanding of SQL, data engineering concepts, ETL/ELT processes, monitoring, incident management, and production support. The resource will work under the supervision of intermediate and senior engineers. Monitor scheduled data pipeline runs, job status, alerts, file arrivals, and data refresh activities. Perform first-level checks for failed jobs, missing files, incomplete loads, data mismatch, and alert notifications. Create, update, and track incidents, service requests, tasks, and change requests in ServiceNow. Run basic SQL queries, perform data checks, validate job outputs, and support source-to-target reconciliation. Collect logs, screenshots, error messages, and supporting details before escalating complex issues to senior resources.

Develop, execute, and maintain automated test scripts for web applications and APIs. Perform manual and automated testing activities, including functional, regression, integration, performance, smoke, and API testing. Support and maintain laboratory facilities and test infrastructure utilized by global engineering teams. Investigate, document, and track software defects using bug-tracking tools. Review and validate technical documentation for accuracy and completeness. Provide technical support and participate in project activities as required. Collaborate with cross-functional and global teams to enhance software quality and testing effectiveness.

Accenture is inviting applications for Associate Software Engineers to contribute to application development, maintenance, and cloud modernization.