Location:

India, work remotely — Global MNC

Engagement:

Contract or a direct FTE hire

Working hours:

IST business hours with an early start (7:00–8:00 AM IST); with some flexibility

About the project

We're building out a cloud data platform for our global MNC client, ingesting data from multiple source systems — including a large, complex enterprise-scale source system (comparable in scale to major ERP platforms) plus several other existing systems and flat files — into a Unified Data Model (UDM) on Azure. The platform is built on Azure Data Factory and Azure Synapse Dedicated SQL Pool, in a hub-and-spoke architecture, feeding purpose-built data marts for different business functions. This isn't a from-scratch build — a substantial part of the framework, architecture, and pipeline patterns already exists for reference.

So the team will extend that existing foundation using established patterns rather than start from zero.

In short: source-system ingestion → UDM/data layers → business-specific data marts, primarily using Azure Data Factory + Azure Dedicated Pool.

About the role

As Data Engineer, you'll be one of the team members building the ingestion pipelines — turning the architecture into working, reliable pipelines that move data from source into the UDM and out into the data marts.





Key Responsibilities

- Build data ingestion pipelines using Azure Data Factory
- Develop data workflows and transformations (e.g. using Databricks)
- Build SQL objects, stored procedures, and data models in Dedicated Pool
- Integrate data from multiple source systems into the platform
- Implement data quality checks and validation logic
- Troubleshoot and support pipelines through deployment

What we're looking for

- 4–8 years of experience as a data engineer, with solid hands-on Azure experience
- Robust working knowledge of Azure Data Factory pipeline development
- Experience with SQL/Pyspark for transformation workflows
- Strong SQL skills, including stored procedures and data modelling in Synapse Dedicated SQL Pool
- Experience integrating data from multiple/disparate source systems
- Comfortable owning data quality/validation and troubleshooting production issues independently

Nice to have

- Experience extracting data from large ERP-type source systems
- Exposure to hub-and-spoke or medallion architecture patterns
- Familiarity with CI/CD for data pipelines (Azure DevOps)

Compensation: Competitive, market-aligned; structured based on engagement model — to be discussed during the process.

📌 Data Engineer - Azure Data Platform (India)
🏢 24-Seven.AI
📍 India