D-TechWorks - Senior Data Engineer - AI Enablement

Description

Job Title :

Senior Data Engineer AI Enablement (Azure)

EXP :

5+ Years

Location :

remote

Notice :

Immediate to 15 days

Employment Type :

Full-Time

Department :

AI Strategy & Engineering

Mandatory Skills

• Azure Data Services,Python, SQL, and PySpark,ETL/ELT pipelines,AI/ML pipelines(NLP, embeddings, and GenAI) , embedding databases and vector stores such as Pinecone, FAISS, or Azure Cognitive Search,CI/CD for data workflows,AI Engineers, Cloud Architects, and DevOps
  

About The Role

We are seeking a Senior data Engineer to support and enable the deployment of enterprise-grade AI solutions across the organization. This role will work in close coordination with the Senior AI/ML Engineer, AI strategy, and Cloud teams to ensure that the data infrastructure, pipelines, and governance mechanisms are in place for scalable, secure, and reliable AI deploymentsparticularly in the Azure OpenAI environment.The ideal candidate will be highly proficient in cloud-native data engineering, experienced with modern data platforms, and able to translate business and AI requirements into robust, production-grade data solutions.

Key Responsibilities

A Senior Data Engineer would be responsible for :

• Collaborate with the AI Engineering team to understand data needs for each use case (structured, unstructured, real-time, batch).
• Ingest, clean, and transform datasets from various enterprise systems into AI-ready formats.
• Build robust ETL/ELT pipelines using Azure-native tools and prepare and maintain embedding databases for RAG (Retrieval-Augmented Generation) models using tools like Pinecone, FAISS, or Azure Cognitive Search.
• Support data ingestion from diverse sources (APIs, databases, SharePoint etc.)
• Work with Cloud and DevOps teams to operationalize AI data pipelines, integrating with ML pipelines and APIs.
• Ensure scalable data infrastructure to handle new and growing AI use cases across the organization.
• Optimize storage and compute costs while maintaining high availability and throughput for AI applications.
• Implement and enforce data governance best practices, including access controls, anonymization, and compliance (e.g., GDPR).
  

What Were Looking For

Essential Criteria :

• 5+ years of experience in data engineering, preferably within enterprise environments.
• Deep knowledge of Azure data services : Data Factory, Synapse, Azure Storage, Azure Data Lake, Event Hubs, Databricks.
• Proficient in Python, SQL , PySpark etc.
• Experience building pipelines for AI/ML applications, especially around NLP, embeddings, or unstructured data.
• Strong understanding of data modelling, pipeline orchestration, and CI/CD for data workflows.
• Familiarity with embedding databases and vector stores used in GenAI applications.
  

Desirable Skills

• Azure Data Engineer Associate or equivalent certification.
• Experience working with data for RAG-based AI architectures and prompt-based systems.
• Bachelor's or Masters in Computer Science, Data Engineering, or a related field.
  

(ref:hirist.tech)