Data Engineer

YASH Technologies; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

YASH Technologies is seeking a Data Engineer (Mid-Senior) with 5+ years of data engineering experience to design and implement scalable data solutions on Microsoft Fabric, focusing on Lakehouse, OneLake, and Data Factory. You will build end-to-end data pipelines, manage OneLake storage, and ensure reliability of Lakehouse and Warehouse environments.

The ideal candidate has hands-on Fabric exposure (1–2 years), strong SQL and Python skills, and practical experience with dimensional modeling, ADLS

Qualifications

• 4+ years of experience in data engineering.
• 1–2 years of hands-on experience with Microsoft Fabric components (Lakehouse, Warehouse, OneLake, Data Factory).
• Strong SQL and Python skills.
• Experience implementing dimensional models and Lakehouse patterns.
• Solid understanding of ADLS Gen2, Azure SQL, and Key Vault in Fabric.
• Experience with Git-based version control and automated deployment workflows for data pipelines.

Skills

Data engineering 4+ yrs

SQL

Python

Microsoft Fabric

Lakehouse pattern

Dimensional modeling

Azure ADLS Gen2

Azure SQL

Key Vault

DevOps for data

Tools

Data Factory

Git

Azure Data Lake storage

Job description

Job Description: Data Engineer (Mid-Senior)

Experience Level: 5+ Years (Microsoft Fabric: 1–2 Years)

Role Overvie

wWe are seeking a Data Engineer with 5+ years of experience to design and implement scalable data solutions on Microsoft Fabric. You will be a key technical contributor, responsible for building end-to-end data pipelines, managing OneLake storage, and ensuring the reliability of Lakehouse and Warehouse environments. This role requires a professional who has already transitioned into the Fabric ecosystem and can independently deliver complex data engineering tasks

.Must-Have Skil

• lsExperience : 4+ years of overall data engineering experienc
• e.Microsoft Fabric : 1–2 years of proven, hands-on experience with core Fabric components (Lakehouse, Warehouse, OneLake, and Data Factory
• ).Core Technical : Expert-level SQL and strong proficiency in PySpar
• k.Data Architecture : Proven experience implementing dimensional models and Lakehouse pattern
• s.Azure Foundations : Solid understanding of ADLS Gen2, Azure SQL, and Key Vault as they integrate with Fabri
• c.Modern DevOps : Experience with Git-based version control and automated deployment workflows for dat