Azure Data Engineer / Azure Expert

XTGLOBAL INFOTECH LIMITED; Visakhapatnam, Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

An IT solutions provider is looking for an experienced Azure Expert to design and manage data pipelines and advanced analytics solutions. The ideal candidate will have in-depth knowledge of Azure Data Factory, Azure Databricks, and Power BI, along with a solid background in data engineering and data modeling practices. Responsibilities include collaborating with teams to deliver actionable insights through reports and dashboards, ensuring data quality, and optimizing performance in a cloud-based environment.

Qualifications

• Proven experience working with Microsoft Azure ecosystem.
• Strong background in data engineering and ETL processes.
• Hands-on experience in SQL, Python, or Scala.
• Strong understanding of data modeling and warehousing.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.

Responsibilities

• Design, build, and maintain data pipelines using Azure Data Factory.
• Develop big data solutions using Azure Databricks.
• Create and publish Power BI dashboards for insights.
• Collaborate with teams to gather requirements.
• Implement data modeling and integration processes.
• Ensure data quality and security.
• Monitor and optimize performance of data solutions.

Skills

Azure Data Factory

Azure Databricks

Power BI

SQL

Python

Scala

Data Engineering

ETL Processes

Problem-solving

Communication

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Azure Synapse Analytics

Azure SQL Database

Job description

Hyderabad / Vizag, India | Posted on 09/22/2025

• Date Opened 09/22/2025
• Job Type Full time
• Work Experience 8+ Years
• Country India

Job Description

Contract / FTE

8+ years experience

UK Shift: 2-11 PM IST

We are seeking a highly skilled Azure Expert with strong expertise in Azure Data Factory, Azure Databricks, and Power BI.

The candidate will be responsible for designing, developing, and managing data pipelines, implementing advanced analytics solutions, and delivering impactful business intelligence dashboards and reports.

Key Responsibilities

• Design, build, and maintain scalable data pipelines using Azure Data Factory for data ingestion, transformation, and orchestration.
• Develop and optimize big data solutions and advanced analytics workflows using Azure Databricks.
• Create, manage, and publish Power BI dashboards and reports to deliver actionable insights to business stakeholders.
• Collaborate with data architects, analysts, and business teams to gather requirements and translate them into technical solutions.
• Implement data modeling, data integration, and ETL/ELT processes within Azure cloud environments.
• Ensure data quality, security, governance, and compliance in all data management activities.
• Monitor, troubleshoot, and optimize performance of data pipelines, analytics processes, and BI solutions.
• Support ad-hoc data requests, business analysis, and reporting needs.

Requirements

• Proven experience working with Microsoft Azure ecosystem (Data Factory, Databricks, Power BI).
• Strong background in data engineering, ETL processes, and big data solutions.
• Hands-on experience in SQL, Python, or Scala for data transformation and analytics.
• Strong understanding of data modeling, data warehousing, and data visualization principles.
• Ability to optimize queries, pipelines, and dashboards for performance and scalability.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills to work with cross-functional teams.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.

Preferred Qualifications

• Microsoft certifications such as Azure Data Engineer Associate, Azure Solutions Architect, or Power BI certification.
• Experience with Azure Synapse Analytics, Azure SQL Database, or other Azure data services.
• Prior experience in data governance, MDM, or cloud security practices.
• Exposure to agile methodologies and DevOps practices for data pipelines.