Azure Big Data Engineer information
See salary details
$15.87 - $22.44
1% of jobs
$22.44 - $29.02
0% of jobs
$29.02 - $35.60
2% of jobs
$35.60 - $42.18
1% of jobs
$42.18 - $48.75
5% of jobs
$54.46 is the 25th percentile. Wages below this are outliers.
$48.75 - $55.33
18% of jobs
$55.33 - $61.91
20% of jobs
The median wage is $62.54 / hr.
$61.91 - $68.49
27% of jobs
$68.62 is the 75th percentile. Wages above this are outliers.
$68.49 - $75.07
13% of jobs
$75.07 - $81.64
8% of jobs
$81.64 - $88.22
4% of jobs
How much do azure big data engineer jobs pay per hour?
As of Aug 14, 2026, the average hourly pay for azure big data engineer in the United States is $62.98, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $70.91 per hour, depending on experience, location, and employer.
An Azure Big Data Engineer is responsible for designing, building, and managing big data solutions using Microsoft Azure cloud technologies. They focus on processing large volumes of data, creating data pipelines, and ensuring data is stored and analyzed efficiently. Their work often involves tools such as Azure Data Lake, Azure Databricks, Azure Synapse Analytics, and Azure Data Factory. Azure Big Data Engineers collaborate with data scientists, analysts, and other IT professionals to enable data-driven decision-making within organizations.
To thrive as an Azure Big Data Engineer, you need expertise in data engineering, cloud computing, and programming languages such as Python or Scala, typically supported by a degree in computer science or a related field. Familiarity with Azure Data Services (like Azure Data Lake, Azure Synapse Analytics, and Azure Databricks), as well as certifications like Microsoft Certified: Azure Data Engineer Associate, is highly valuable. Strong analytical thinking, problem-solving, and communication skills help you collaborate effectively with cross-functional teams and translate business needs into technical solutions. These skills and qualities are essential for building scalable, reliable data pipelines that drive business insights and innovation in cloud environments.
Azure Big Data Engineers often encounter challenges such as ensuring data consistency and quality when integrating disparate data sources like on-premises databases, cloud storage, and third-party APIs. Handling varying data formats and latency issues can also complicate data pipelines. To overcome these challenges, engineers typically use Azure Data Factory for orchestration, implement robust data validation, and collaborate closely with data architects and business analysts to align on integration requirements.
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