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Job Description: Sr Analyst – Data & Analytics

Data Engineering with Applied AI | 5–7 Years of Experience

Role Overview

We are seeking a Data Engineer with 5–7 years of experience in building scalable data platforms and preliminary hands-on exposure to AI solutions.

Key Responsibilities

·   Develop and automate high-performance data processing systems to drive business growth and improve product experience.

·   Translate business requirements into technical solutions with end-to-end ownership.

·   Promote high-quality software engineering practices for building data infrastructure and pipelines at scale.

·   Build reliable, efficient, testable, and maintainable data pipelines.

·   Design and develop data pipelines using metadata-driven ETL tools and open-source data processing frameworks.

·   Provide production support, resolve high-priority incidents, and troubleshoot development and coding issues.

·   Work with cross-functional teams to enable insights across the data lifecycle.

AI Responsibilities

·   Support data pipelines and data preparation for AI and Generative AI applications.

·   Build and maintain integrations with Azure OpenAI and other Azure AI services.

·   Develop and support RAG (Retrieval-Augmented Generation) workflows, including document ingestion, embeddings, and search indexing.

·   Collaborate with business and technical teams to implement AI-enabled solutions and enterprise copilots.

·   Ensure AI solutions adhere to data governance, security, privacy, and Responsible AI standards.

Minimum Qualifications

·   5–7 years of experience in data engineering, including SQL-based design and development of scalable, robust data pipelines.

·   Experience with large-scale data lake and data engineering projects.

·   Proficiency in advanced SQL and SQL performance tuning.

·   Strong experience in Python or another programming language used to process large datasets.

·   Experience with ETL/ELT, data modeling, STAR schemas, metadata management, data quality, and production support.

·   Working knowledge of REST APIs, JSON, authentication patterns, and integration of cloud-based services.

·   Foundational understanding of machine learning and Generative AI concepts, including large language models, embeddings, vector search, prompt engineering, and RAG.

·   Ability to troubleshoot end-to-end data and AI pipelines and work with users to resolve issues.

Preferred Qualifications

·   BE- Computer Science with healthcare exposure.

·   Experience with AWS data technologies such as Amazon S3 or Amazon Redshift is beneficial where relevant to the existing data landscape.

·   Basic understanding of LLMs, Prompt Engineering, Embeddings, Vector Search, and RAG concepts.

·   Exposure to Azure OpenAI Service, Azure AI Search, Azure Databricks, or Azure Machine Learning.

·   Experience working on chatbot, copilot, or AI assistant solutions is preferred.

·   Familiarity with frameworks such as Semantic Kernel, LangChain, or similar orchestration tools.

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