Data Engineer – Microsoft Fabric / Azure

VMC Soft Technologies, Inc

Bengaluru

On-site

INR 1,400,000 - 2,100,000

Full time

31 hours ago

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Job summary

VMC Soft Technologies, Inc. is seeking a Data Engineer for designing and delivering scalable data platforms using Microsoft Fabric or Azure Data Stack in Bengaluru. The role focuses on building ETL/ELT pipelines, modeling data for analytics, and enabling Power BI reporting.

You will implement and optimize data pipelines with Python/PySpark, work with Azure Data Lake, and collaborate with cross-functional teams to meet production standards and governance requirements.

Qualifications

4–6 years of Data Engineering / Data Platform experience.
Microsoft Fabric OR Azure Data Stack expertise.
Microsoft Fabric Lakehouse / Data Factory / Notebooks OR Azure ADF / ADLS Gen2 / Synapse / Databricks.
Azure Data Lake / Blob Storage experience.
Strong SQL skills.
Python & PySpark for data processing and pipelines.
ETL/ELT pipeline development experience.
Data modeling for analytics and reporting.
Power BI integration and data prep.
Git / Azure DevOps / GitHub for source control.
Basic cloud security and access management understanding.

Responsibilities

Design, develop, and maintain scalable ETL/ELT data pipelines.
Build data solutions using Microsoft Fabric Lakehouse, Data Factory, and Notebooks or Azure services.
Develop and optimize complex SQL queries for data transformation and analytics.
Use Python and PySpark for data processing and pipeline development.
Design and implement data models for analytics and reporting.
Prepare and integrate data for Power BI reporting and analytics.
Work with Azure Data Lake / Blob Storage and related cloud data services.
Ensure data pipelines are reliable, scalable, secure, and production ready.
Use Git, Azure DevOps, or GitHub for source control and CI/CD practices.
Collaborate with data/platform teams and business stakeholders to translate requirements into solutions.
Apply data quality, validation, error handling, and performance optimization practices.
Document data pipelines, data models, assumptions, dependencies, and processes.
Follow cloud security and governance best practices.

Skills

Microsoft Fabric

Azure Data Stack

SQL

Python

PySpark

ETL/ELT pipeline development

Data modeling

Power BI integration

Azure Data Lake / Blob Storage

Git / Azure DevOps / GitHub

Data pipelines

Tools

Databricks

Azure Data Factory

Azure Synapse Analytics

Azure Databricks

Power BI

GitHub

Job description

Job Description

Job Description Data Engineer / Microsoft Fabric

Job Title: Data Engineer Microsoft Fabric / Azure

Experience: 4 6 Years

Location: Bangalore

Skill: EIS Embedded Software/Firmware Development

Role Overview

We are looking for an experienced Data Engineer with strong expertise in Microsoft Fabric or Azure Data Stack to design, develop, and maintain scalable data platforms and ETL/ELT pipelines. The candidate will work closely with data engineers, domain experts, and platform teams to deliver reliable, production-ready data solutions.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT data pipelines.
Build data solutions using Microsoft Fabric Lakehouse, Data Factory, and Notebooks or Azure services such as ADF, ADLS Gen2, Synapse, and Databricks.
Develop and optimize complex SQL queries for data transformation and analytics.
Use Python and PySpark for data processing and pipeline development.
Design and implement appropriate data models for analytics and reporting.
Prepare and integrate data for Power BI reporting and analytics.
Work with Azure Data Lake / Blob Storage and related cloud data services.
Ensure data pipelines are reliable, scalable, secure, and production ready.
Use Git, Azure DevOps, or GitHub for source control and CI/CD practices.
Collaborate with data/platform teams and business stakeholders to understand requirements and translate them into technical solutions.
Apply data quality, validation, error handling, and performance optimization practices.
Document data pipelines, data models, assumptions, dependencies, and technical processes.
Follow cloud security, access management, and governance best practices.