Data Engineer

Rail Infotech India; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Rail Infotech India is seeking an experienced Data Engineer with 5+ years to design, build, and scale our data infrastructure using Azure data services and Microsoft Fabric.

You will architect end-to-end data pipelines, optimize complex SQL transformations, and partner with analytics, product, and engineering teams to deliver reliable data solutions that empower business intelligence and data-driven decision making.

Qualifications

• 5+ years of hands-on data engineering experience.
• Strong experience with Azure Data Factory, ADLS and Microsoft Fabric.
• Proficiency in SQL and PySpark.

Responsibilities

• Data Pipeline Engineering: design, develop, maintain, and optimize scalable end-to-end data pipelines using Azure data services and Fabric.
• Modern Data Architecture: work with Fabric components like Data Factory, Lakehouse, Warehouse and related capabilities.
• Data Transformation & Optimization: write and fine-tune complex SQL queries and data transformation logic for performance and integrity.
• Collaboration & Scale: partner with analytics, product and engineering teams to deliver reliable data solutions powering BI and decision-making.

Job description

We are seeking an experienced and driven Data Engineer with 5+ years of hands‑on expertise to design, build, and scale our next‑generation data infrastructure. In this role, you will play a critical part in architecting robust data pipelines, optimizing complex transformations, and maximizing the value of our cloud data assets using modern Microsoft platforms.

Key Responsibilities

• Data Pipeline Engineering: Design, develop, maintain, and optimize scalable, reliable, and secure end-to-end data pipelines using Azure data services and Microsoft Fabric.
• Modern Data Architecture: Work extensively with core Microsoft Fabric components, including Fabric Data Factory, Lakehouse, Warehouse, and other advanced data engineering capabilities.
• Data Transformation & Optimization: Write, debug, and fine-tune complex SQL queries, stored procedures, views, and intricate data transformation logic to ensure high performance and data integrity.
• Collaboration & Scale: Partner closely with analytics, product, and engineering teams to understand data requirements and deliver reliable data solutions that power business intelligence and decision‑making.

Required Key Skills & Tech Stack

• Core Skills: Microsoft Fabric Data Factory, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), PySpark, Advanced SQL.
• Data Concepts: ETL/ELT pipeline development, Data Lakehouse & Warehouse architectures, performance tuning, and complex data transformation.