Role Overview:

We are looking for a practical, hands-on Microsoft Fabric Data Engineer to help build, improve and maintain the data layer that supports One Retail Group’s finance, inventory, supply chain, ecommerce, marketplace and reporting processes.

Based from our Bengaluru office, you will work with our Head of IT and teams across the UK, India, China and other markets. You will help connect key data sources into Microsoft Fabric, including Business Central, ecommerce platforms, marketplaces, supply chain systems, warehouse partners, operational tools and reporting sources.

This is not a narrow reporting role. We are not looking for someone who only builds dashboards. We need someone who can own the data pipelines underneath, make sure data is accurate and reliable, investigate issues properly, and help the business trust the numbers it uses to make decisions.

You will work across Fabric lakehouses, OneLake data structures, notebooks, pipelines, APIs, data models and Power BI reporting layers. The role will involve improving existing work as well as building new data flows where needed. You should be comfortable dealing with imperfect systems, manual processes and business-critical data where accuracy matters.

We need someone who can understand a data problem, identify the source, build a practical solution, test it properly, document it clearly and support it after release.

Key Responsibilities:

Microsoft Fabric and Data Engineering:

• Build, maintain and improve Microsoft Fabric lakehouses, OneLake data structures, notebooks, pipelines and dataflows.

• Develop reliable data pipelines using SQL, Python, PySpark and Microsoft Fabric tools.

• Ingest and transform data from Business Central, APIs, ecommerce platforms, marketplaces, supply chain systems, warehouse partners and operational tools.

• Maintain clear raw, cleaned and reporting-ready data layers.

• Monitor pipeline runs, investigate failures and improve reliability over time.

• Help manage refresh schedules, performance, data quality checks and exception handling.

• Use source control, testing and documentation so changes can be reviewed and safely maintained.

API Integrations and Business Data:

• Connect to external APIs and manage pagination, rate limits, retries, missing data and duplicate prevention.

• Support marketplace, ecommerce, supply chain and inventory data flows, including Amazon and future commercial platforms.

• Work carefully with Business Central data, especially where it affects finance, inventory, sales, purchasing, fulfilment, replenishment or operational reporting.

• Understand that data accuracy matters more than simply making a pipeline run.

• Identify whether an issue is caused by the source system, the data pipeline, Business Central, Power BI or a business process.

Power BI and Reporting Models:

• Build and maintain Power BI semantic models, datasets and reporting layers.

• Improve report performance, refresh reliability and data model clarity.

• Support dashboards used by finance, operations, supply chain, commercial and leadership teams.

• Make sure reports are based on trusted, checked data rather than fragile manual workarounds.

• Turn raw data into useful reporting outputs without losing auditability or control.

Data Quality and Controls:

• Build checks for missing data, duplicate records, late-arriving data and unexpected changes.

• Create clear alerts or review outputs when something needs attention.

• Document important data rules in plain English.

• Support controlled releases and testing before changes affect live reporting.

• Help the business trust the data by proving what has been checked, not just saying a process has completed.

Future Ownership:

• Help One Retail Group build stronger internal ownership of Microsoft Fabric and reporting data.

• Reduce dependence on one-off fixes, manual workarounds and undocumented notebooks.

• Improve the maintainability of existing Fabric work rather than rebuilding everything from scratch.

• Work with the Head of IT to create practical standards for Fabric development, testing, monitoring and documentation.

• Use AI-assisted tools responsibly to speed up analysis, debugging and documentation, while still owning the quality and accuracy of the final output.

Ideal Candidate:

• 4+ years’ experience in data engineering, BI engineering or a similar data-focused role.

• Hands-on experience with Microsoft Fabric, OneLake, lakehouses, notebooks, pipelines or similar modern data platforms.

• Strong SQL skills and good working knowledge of Python or PySpark.

• Experience connecting to APIs and maintaining reliable data pipelines.

• Experience with Power BI semantic models, datasets, dashboards or reporting data models.

• Understands data quality, duplicate prevention, refresh reliability and exception handling.

• Comfortable working with business-critical finance, inventory, supply chain, sales, ecommerce or operational data.

• Able to investigate issues properly and explain root causes clearly.

• Practical, careful and commercially aware.

• Comfortable working with both technical and non-technical stakeholders.

• Experience with Microsoft Dynamics 365 Business Central data would be a strong advantage.

• Experience with ecommerce, marketplace, warehouse, supply chain, finance or retail data would be beneficial.

• Experience with Azure data tools such as Azure Data Factory, Azure Data Lake, Synapse, Azure SQL or Databricks would be beneficial.

• Microsoft Fabric certifications would be useful, but hands-on experience is more important.