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Senior Azure Engineer

Fractal Analytics
Posted on
Fractal Analytics logo

Experience
6 - 9 yrs
Salary (CTC)
₹12L - ₹20L
Job Location
Bengaluru, India
Vacancy
1
Designation
Azure Data Engineer
Job Type
ONSITE

Job Description

Position: Azure Data Engineer

Location: Any Fractal Offshore Locations preferred Bangalore

Experience Level: Grade basis

Job Summary

We are seeking a skilled Azure Data Engineer with around 4+ years of experience to join our team. This role is suited for a data professional who can independently design, develop, and manage data pipelines on Azure, implementing data solutions that align with business needs. The candidate will have hands-on expertise across the Azure data stack, with a strong focus on optimizing data workflows and implementing best practices. Should have python knowledge.

Responsibilities

Data Solution Design and Implementation
Develop and maintain scalable ETL and ELT processes on Azure using Azure Data Factory, Databricks, and Synapse Analytics.
Work independently to translate business requirements into technical data solutions, designing effective and reliable data models.
Collaborate with cross-functional teams to ensure data solutions align with business objectives and technical standards.
Data Pipeline Development and Optimization
Design and optimize end-to-end data pipelines, leveraging Medallion architecture and Lakehouse principles.
Implement data transformations using PySpark and Azure Databricks, ensuring high-performance and quality data integration.
Data Storage and Management
Manage data within Azure Data Lake Storage (ADLS Gen2) and Azure SQL Database, ensuring accessibility and compliance with security standards.
Design data models and structures to support data analysis and reporting across different business functions.
Troubleshooting and Quality Assurance
Identify and resolve performance bottlenecks in data pipelines, implementing solutions to enhance efficiency and scalability.
Conduct quality assurance tests, ensuring data integrity, accuracy, and security compliance in the data pipeline.
Documentation and Best Practices