Develop, schedule, and manage ETL processes using SSIS and Azure Data Factory (ADF)
Build and optimize data models and OLAP cubes using SSAS and Azure Analysis Services
Design and deploy reports using SSRS and Power BI
Migrate on-premises SQL workloads to Azure SQL, Data Lake, and Synapse
Build scalable data pipelines and processing workflows using Databricks (PySpark)
Write complex T-SQL queries, stored procedures, functions, and triggers.
Implement DevOps pipelines for data deployment and automation using Azure DevOps
Collaborate with stakeholders to convert business requirements into technical solutions.
Track and resolve issues through ServiceNow, JIRA, or ALM
Maintain technical documentation including Low-Level Design and testing artifacts.
Incorporate temporal dynamics into modeling strategy to enhance prediction accuracy over time.
Design and implement scalable ML pipelines using Azure AI Hub, Foundry, Blob Storage, and Cosmos DB.
Collaborate with architecture and platform teams to ensure smooth lift-and-shift deployment of the solution into client environments.
Integrate outputs with Azure OpenAI (GPT-4o) to build conversational interfaces via Microsoft Copilot Studio or Power Apps.
Evaluate model performance using robust metrics (accuracy, AUC-ROC, ranking correlation).
Work closely with stakeholders to translate business requirements into ML model specifications and insights delivery.
Stay up to date with advances in NLP, ranking models, and Azure ML ecosystem.

Deep experience with MSBI tools: SSIS, SSRS, SSAS, Power BI




Advanced SQL skills and experience with SQL Server (2008R2 2019)
Strong knowledge of Azure PaaS services: Data Factory, Databricks, Cosmos DB, Analysis Services
Programming in Python and C#
Hands-on experience with CI/CD and Azure DevOps
Sound knowledge of data warehousing, data modeling, and ETL principles
Robust communication and analytical skills with a proactive mindset
- Azure Data Factory - Databricks
- Azure Synapse - Data pipeline integration
Enterprise-level BI solutions - Integration with Azure Synapse, Purview, and Power BI - Advanced reporting and dashboard design

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Deep proficiency in Python, with expertise in transformers, Python/TensorFlow, Hugging Face, and data science libraries (pandas, scikit-learn).
Hands-on experience with BERT, pairwise learning, and ranking models.
Prior exposure to temporal modeling techniques (e.g., sliding windows, time-based feature engineering).
Strong experience with the Azure ecosystem, including:
o Azure AI Hub and Foundry
o Azure Machine Learning
o Azure OpenAI
o Azure Cosmos DB and Blob Storage
o Azure Monitor and Application Insights
Experience designing or integrating generative AI solutions (e.g., GPT-4, Claude, Gemini).
Familiarity with CRISP-DM methodology or other structured data science lifecycles.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Azure Data Engineer - Consultant/Senior Consultant (West Bengal)
🏢 Grant Thornton
📍 West Bengal