Data Engineer- Azure Fabric

PalTech; Hyderabad; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

PalTech in Hyderabad, India seeks a Senior Microsoft Fabric Data Engineer to lead data engineering initiatives using Fabric components and Azure data services. You will design and optimize enterprise data pipelines, data lakes, and warehouses, delivering business-ready datasets for analytics.

The role emphasizes PySpark, SQL, and Power BI proficiency, with a focus on data migration, modernization, and reliable data platforms across the Azure stack.

Qualifications

• Strong expertise in PySpark, SQL, Data Warehousing and Power BI.
• Experience with Microsoft Fabric components and Azure data services.

Responsibilities

• Enterprise-level data pipelines and workflows.
• Optimized Lakehouse and Data Warehouse solutions.
• Reliable and secure data platforms.
• Business-ready datasets for reporting and analytics.
• Automated monitoring and data quality frameworks.

Skills

Data Science

Real-Time Analytics

Data Engineering

Tools

OneLake

Data Factory

Lakehouse

Data Warehouse

Power BI

SQL

Python

PySpark

Spark SQL

T-SQL

Azure Data Services

Azure Data Lake Storage

Azure Synapse Analytics

Azure Databricks

Azure SQL Database

Job description

Job Description:

Required Skills & Qualifications

• Strong experience with Microsoft Fabric components:
  • OneLake
  • Data Factory
  • Lakehouse
  • Data Warehouse
  • Data Engineering
  • Data Science
  • Real-Time Analytics
  • Power BI
• Proficiency in:
  • SQL
  • Python
  • PySpark
  • Spark SQL
  • T-SQL
• Experience with:
  • Azure Data Services
  • Azure Data Lake Storage (ADLS)
  • Azure Synapse Analytics
  • Azure Databricks
  • Azure SQL Database
  • Power BI

Experience Requirements

Senior Microsoft Fabric Data Engineer

• 4+ years of overall data engineering experience.
• 2+ years of hands-on Microsoft Fabric implementation experience.
• Strong expertise in PySpark, SQL, Data Warehousing, and Power BI.
• Experience leading data migration and modernization initiatives.

Key Deliverables

• Enterprise-level data pipelines and workflows.
• Optimized Lakehouse and Data Warehouse solutions.
• Reliable and secure data platforms.
• Business-ready datasets for reporting and analytics.
• Automated monitoring and data quality frameworks.