Staff Engineer, Azure Data Engineer

We're Nagarro.

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (17500 experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

REQUIREMENTS:

• Total experience: 6+ years.
• Excellent knowledge and experience in Azure data engineer.
• Strong working experience with architecture and development in

  Spark, Python, Azure Databricks, Azure Datafactory, Data Modeling, GenAI.

• Strong proficiency in Azure data services, including:

1. Azure Data Factory / Synapse
2. Azure Databricks / Spark
3. Azure Data Lake Storage
4. Azure Functions / Logic Apps
5. Azure Key Vault, Monitoring, Networking

• Hands-on experience working with vector databases, especially:

1. Azure AI Search
2. Cosmos DB (vector search)
3. Pinecone, Weaviate, or similar

• Experience building

  GenAI or LLM-based applications

  , including:

1. Retrieval-Augmented Generation (RAG)
2. Embeddings pipelines
3. Prompt engineering fundamentals
4. LLM orchestration frameworks (LangChain, Semantic Kernel, etc.)

RESPONSIBILITIES:

• Writing and reviewing great quality code
• Understanding the clients business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements
• Mapping decisions with requirements and be able to translate the same to developers
• Identifying different solutions and being able to narrow down the best option that meets the clients requirements
• Defining guidelines and benchmarks for NFR considerations during project implementation
• Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
• Understanding and relating technology integration scenarios and applying these learnings in projects.