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Azure Data Engineer

Data PlatformExperts
Remote

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Job details

Permanent | Full-time
₹10,00,000 - ₹15,00,000 a year
3 days ago

Benefits

Work from home

Qualifications

CI/CD
Power BI
Data modelling
Azure
DevOps
Spark
SQL
Analysis skills
Machine learning
Version control systems
Continuous integration
Azure Certification
Kafka
AI
Communication skills
Data warehouse
Python

Full job description

Work Mode: Permanent Work from Home / Hybrid – Hyderabad
Work Timing: 4:00 PM – 1:00 AM ISTJob DescriptionWe are looking for a skilled and motivated AI Azure Data Engineer with strong expertise in the Microsoft Azure data ecosystem and Power BI. The ideal candidate must have hands-on experience with Databricks or Microsoft Fabric and hold a valid certification in either.The candidate will be responsible for designing, developing, and deploying scalable data pipelines, integrating AI/ML solutions, building analytical data models, and developing insightful Power BI dashboards and reports.Key Responsibilities

Design and develop end-to-end data pipelines using Azure Data Factory, Databricks, or Microsoft Fabric.
Integrate structured and unstructured data from various sources into Azure Data Lake, Lakehouse, or Data Warehouse environments.
Develop and optimize data pipelines for performance, scalability, reliability, and data quality.
Design and implement Power BI dashboards, reports, and interactive visualizations based on business requirements.
Develop Power BI data models, relationships, calculated columns, measures, and DAX expressions.
Connect Power BI with Microsoft Fabric, Azure Synapse, Databricks, Azure SQL, Data Lake, and other data sources.
Implement Power BI row-level security (RLS), workspace management, refresh schedules, and deployment best practices.
Collaborate with Data Scientists and AI teams to deploy and operationalize ML models.
Implement data governance, security, quality, and compliance standards across data and analytics solutions.
Develop and maintain CI/CD pipelines for data and Power BI projects using DevOps best practices.
Optimize Power BI reports and datasets for performance and scalability.
Collaborate with business stakeholders and analytics teams to translate requirements into effective data and reporting solutions.

Required Skills & Qualifications

Minimum 5+ years of experience in Data Engineering within the Azure ecosystem.
Strong hands-on experience with Power BI, including dashboards, reports, data modeling, and DAX.
Strong proficiency in Azure Data Factory, Azure Synapse, Azure Data Lake, Databricks, or Microsoft Fabric.
Hands-on experience with Spark, Python, and SQL.
Experience working with Power BI Service, Power Query, semantic models, and data refresh.
Experience integrating Power BI with Azure/Fabric data platforms.
Experience in AI/ML model integration or operationalization is a plus.
Proficiency in version control systems and Azure DevOps.
Strong understanding of data modeling, data warehousing, ETL/ELT processes, and analytics.

Certifications – MandatoryAny one of the following certifications:

Microsoft Certified: Azure Data Engineer Associate
Databricks Certified Data Engineer Associate/Professional
Microsoft Fabric Analytics Engineer Associate

Power BI certification (PL-300) is preferred.Preferred Skills

Experience with Microsoft Fabric and Power BI integration.
Experience with real-time data processing using Azure Stream Analytics, Kafka, or similar technologies.
Exposure to Azure AI services such as Azure Cognitive Services and Azure Machine Learning.
Experience developing enterprise-level Power BI dashboards and reporting solutions.
Knowledge of Power BI performance optimization and governance.
Strong problem-solving, analytical, and communication skills.

Pay: ₹1,000,000.00 - ₹1,500,000.00 per year

Benefits:

Work from home

Application Question(s):

Are you ok with work timings 4 pm to 1 am (Midnight )permanent work from Home ?
How much notice period do you have ?
What is your expected CTC ?

Experience:

Azure: 6 years (Required)
Fabric: 3 years (Required)
Power BI: 2 years (Required)

Work Location: Remote

Quick apply

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