Data Engineer – AI

Everest Technologies, Inc

Data Engineer supporting enterprise AI and Generative AI initiatives by building scalable, secure, and AI-ready data platforms at ETech. Collaborating with Data Engineers, AI Engineers, and Data Scientists.

Posted 7/23/2026full-timeRemote • 🇮🇳 IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building scalable data platforms and pipelines for AI applications, with strong proficiency in Azure Databricks, Snowflake, and Python. Capable of integrating diverse data sources and implementing data governance and quality practices to support enterprise AI initiatives.

Highest-signal resume keywords

Azure DatabricksSnowflakePythonELT/ETL PipelinesAI & Azure AI Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSQLPySparkData WarehousingDimensional ModelingData Lake ArchitecturesREST API IntegrationData QualityData GovernancePerformance Tuning

Soft Skills

CollaborationProblem-SolvingAgile/Scrum Experience

Tools & Technologies

Azure Data FactoryGitAzure DevOpsCI/CD PipelinesAzure Machine LearningMicrosoft AI FoundryAzure OpenAI ServiceAzure AI SearchMicrosoft Copilot Studio

Industry Keywords

Generative AIRetrieval-Augmented GenerationAI-Powered ApplicationsEnterprise DataMachine Learning

Tech Stack

Tools & technologies

AzureCloudERPETLPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Support enterprise AI and Generative AI initiatives by building scalable, secure, and AI-ready data platforms.
Partner with Data Engineers, AI Engineers, Data Scientists, and business stakeholders to develop high-quality data pipelines.
Enable Retrieval-Augmented Generation (RAG) solutions and prepare enterprise data for AI-powered applications.
Design, develop, and maintain scalable data pipelines using Azure Databricks, Snowflake, and Azure Data Factory.
Build ELT/ETL pipelines to ingest data from ERP, CRM, manufacturing, supply chain, and other enterprise applications.
Develop AI-ready datasets that support machine learning and Generative AI use cases.
Integrate structured, semi-structured, and unstructured data into centralized data platforms.
Collaborate with AI Engineers to expose enterprise data securely to LLM-powered applications.
Optimize data models, transformations, and query performance for analytics and AI workloads.
Implement data quality, governance, lineage, monitoring, and security best practices.
Build reusable data transformation frameworks using Python, SQL, Spark, and dbt (if applicable).
Develop REST API integrations to support AI services and enterprise applications.
Participate in architecture discussions, code reviews, CI/CD implementations, and Agile ceremonies.
Support production deployments, monitoring, troubleshooting, and performance tuning.

Requirements

What you’ll need

5+ years of experience in Data Engineering
Strong hands-on experience with Azure Databricks and Snowflake
Proficiency in Python, SQL, and PySpark
Experience building scalable ELT/ETL pipelines using Azure Data Factory
Strong understanding of data warehousing, dimensional modeling, and data lake architectures
Experience working with REST APIs and integrating cloud-based services
Familiarity with Git, Azure DevOps, and CI/CD pipelines
Experience working in Agile/Scrum environments
AI & Azure AI Experience (Required)
Experience supporting enterprise AI or Generative AI initiatives
Working knowledge of Azure Machine Learning (Azure ML)
Experience with Microsoft AI Foundry (Azure AI Foundry) for AI solution development and orchestration
Experience integrating Azure OpenAI Service into enterprise applications
Knowledge of Azure AI Search for enterprise search and Retrieval-Augmented Generation (RAG) solutions
Exposure to Microsoft Copilot Studio for developing AI-powered copilots and conversational experiences
Understanding of vector search, embeddings, prompt engineering, and LLM integration
Experience preparing enterprise data for AI model training, inference, and knowledge retrieval.

Benefits

Comp & perks

Flexible work arrangements
Professional development
Remote work options