Senior Azure Data Engineer

Fractal; Bengaluru; On-site; INR 1,400,000 - 2,100,000; Full time

Job summary

Fractal is seeking an Azure Data Engineer to design, build, and maintain robust data pipelines and infrastructure across multiple Indian offices including Bengaluru.

The role demands 6-9 years of experience and expertise in Azure Data Factory, ADLS2, Databricks, Python, PySpark, and DevOps practices to drive data quality and scalable solutions.

Qualifications

• 6-9 years of data engineering experience.
• Experience building data pipelines and data infrastructure.
• Proficiency with Azure data services and Python-based tools.

Responsibilities

• Design, develop, and maintain data infrastructure and systems.
• Develop and maintain data pipelines to ingest data and ensure quality.
• Design data models and database schemas to support business objectives.
• Partner with cross-functional teams to identify data requirements.
• Manage and optimize distributed data storage solutions.
• Establish best practices and standards for data engineering.

Tools

Azure

ADF

ADLS2

Databricks

Python

PySpark

DevOps

AI factory

Ultimate

Pygentic

Job description

Job Description:

It’s fun to work in a company where people truly BELIEVE in what they are doing!

We’re committed to bringing passion and customer focus to the business.

Role- Azure Data Engineer

Locations- Pune, Mumbai, Gurgaon, Noida, Chennai, Coimbatore, Bangalore

Experience 6-9years

We value our talented employees, and whenever possible strive to help one of our associates grow professionally before recruiting new talent to our open positions.

Our people make all the difference in our success.

Responsibilities

• Designing, developing, and maintaining data infrastructure and systems.
• Design, develop, and maintain our data infrastructure and systems
• Develop and maintain data pipelines to ingest data, ensure data quality and integrity
• Design and implement data models and database schemas to support business objectives
• Develop and maintain data pipelines to support data processing and analysis
• Partner with cross-functional teams to identify and prioritize data requirements and use cases
• Manage and optimize distributed systems and data storage solutions
• Develop and maintain best practices and standards for data engineering within the organization

Mandatory

• Azure, ADF, ADLS2, Databricks, Python, PySpark, DevOps, P&G frameworks like AI factory, Ultimate, Pygentic

Requirements: