Data Engineer

Hireginie; Bengaluru; On-site; INR 1,500,000 - 2,700,000; Full time

Job summary

Hireginie is seeking a Data Engineer in Bengaluru to design and optimize scalable data solutions on Microsoft Azure. You will build ETL/ELT pipelines using Azure Data Factory, Databricks, PySpark, and Synapse Analytics, shaping modern Lakehouse architectures and data warehouses.

Collaborate with cross-functional teams to deliver data-driven solutions, ensure data quality and governance, and optimize performance, cost, and security across the data platform.

Qualifications

• 3-5 years of experience in Azure Data Engineering.
• Hands-on experience with Azure Databricks, Azure Synapse Analytics, and Azure Data Factory.
• Strong understanding of modern cloud-based data platforms and enterprise data architecture.

Responsibilities

• Design, develop, and implement scalable end-to-end data engineering solutions on Microsoft Azure.
• Build and optimize ETL/ELT pipelines using Azure Data Factory and Azure Databricks.
• Develop data transformation workflows using Spark and PySpark.
• Design and maintain data warehouses, Lakehouse, and modern data platform architectures.
• Work with Azure Synapse Analytics for enterprise data warehousing and analytical workloads.
• Integrate structured and unstructured data from multiple data sources.
• Optimize data processing performance, scalability, and cost efficiency.
• Implement data quality, security, governance, and monitoring best practices.
• Collaborate with business stakeholders, architects, and cross-functional teams to deliver data-driven solutions.
• Troubleshoot production issues and continuously improve platform reliability and performance.
• Stay up to date with Azure data services and recommend best practices for modern data platforms.

Skills

Cross-functional collaboration

Client-facing communication

Analytical thinking

Education

Bachelor's degree in Technology

Tools

Azure Data Factory

Azure Databricks

Azure Synapse Analytics

PySpark

Job description

About Our Client

We are a global technology consulting company delivering digital transformation, process automation, and data-driven solutions to help organizations improve efficiency and make smarter business decisions.

Job Title

Data Engineer

Experience

3-5 years

Educational Qualification

Bachelors in Technology or related field.

About the role

The Data Engineer will build and optimize scalable data solutions on Microsoft Azure using Azure Data Factory, Databricks, PySpark, and Synapse Analytics. The role focuses on developing ETL/ELT pipelines, modern Lakehouse and data warehouse architectures, data integration, and ensuring performance, quality, security, and governance.

Responsibilities

• Design, develop, and implement scalable end-to-end data engineering solutions on Microsoft Azure.
• Build and optimize ETL/ELT pipelines using Azure Data Factory and Azure Databricks.
• Develop data transformation workflows using Spark and PySpark.
• Design and maintain data warehouses, Lakehouse, and modern data platform architectures.
• Work with Azure Synapse Analytics for enterprise data warehousing and analytical workloads.
• Integrate structured and unstructured data from multiple data sources.
• Optimize data processing performance, scalability, and cost efficiency.
• Implement data quality, security, governance, and monitoring best practices.
• Collaborate with business stakeholders, architects, and cross-functional teams to deliver data-driven solutions.
• Troubleshoot production issues and continuously improve platform reliability and performance.
• Stay up to date with Azure data services and recommend best practices for modern data platforms.

Requirements

• 3-5 years of experience in Azure Data Engineering.
• Hands-on experience with Azure Databricks, Azure Synapse Analytics, and Azure Data Factory.
• Strong understanding of modern cloud-based data platforms and enterprise data architecture.
• Experience working in client-facing consulting or digital transformation projects is preferred.
• Ability to work independently and collaborate effectively with cross-functional teams in a fast-paced environment.