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# Senior Data Engineer - Azure/ Fabric/ Databricks

- **Company:** Mastech Digital, Inc.
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Microsoft Azure, Cloud Computing, Code Review, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Warehousing, Software Debugging, DevOps, Python (Programming Language), Performance Tuning, Azure Data Lake, SQL Databases, Data Logging, Data Processing, Data Ingestion, Azure Data Factory, Microsoft Fabric, Data Lakes, Pyspark, Data Management, Azure Synapse Analytics, Data Pipelines, Databricks
- **Published:** September 4, 2026
- **Apply:** http://datafrenzy.com/Job/Display?jobNum=24084627

## About the Role

Role Description: The Senior Data Engineer must have 6+ years of experience. We are seeking a highly skilled Senior Data Engineer to join the Data Cloud team. The ideal candidate should possess strong data engineering expertise with hands-on experience in Python, Azure Synapse Analytics, Microsoft Fabric, Databricks, and modern cloud-based data platforms.

You should be capable of independently designing, developing, optimizing, and supporting scalable data solutions while working closely with business and technical stakeholders., Strong Python programming experience

 - PySpark

 - Azure Synapse Analytics

 - Microsoft Fabric

 - Databricks

 - SQL

 - Azure Data Factory (ADF)

 - Azure Data Lake Storage (ADLS)

 - Delta Lake

 - Data Warehousing Concepts

 - ETL / ELT Development

 - Data Modeling

 - CI/CD and DevOps practices

 - Performance Optimization and Troubleshooting

Preferred Experience:

 - Banking or Financial Services domain experience

 - Regulatory reporting and analytics platforms

 - Medallion Architecture (Bronze, Silver, Gold)

 - Large-scale cloud data migration and modernization projects

Key Expectations:

 - Strong engineering and problem-solving capabilities

 - Ability to work independently with minimal supervision

 - Experience handling complex data transformation and integration scenarios

 - Strong debugging, troubleshooting, and optimization skills

 - Excellent communication and stakeholder management skills

## Description

Analyze business requirements and design scalable data engineering solutions.

 - Design, develop, and maintain robust data pipelines and ETL/ELT frameworks.

 - Build and optimize data ingestion, transformation, and processing workflows using Python and PySpark.

 - Develop data solutions using Azure Synapse Analytics, Microsoft Fabric, and Databricks.

 - Implement scalable data lake and data warehouse architectures.

 - Develop reusable, metadata-driven, and parameterized data pipelines.

 - Perform complex data transformations, aggregations, joins, and data quality validations.

 - Optimize pipeline performance and troubleshoot data processing issues.

 - Implement monitoring, logging, and error-handling frameworks.

 - Work with structured and semi-structured data sources across cloud and on-premises platforms.

 - Support production incidents, root cause analysis, and performance tuning activities.

 - Collaborate with cross-functional teams to deliver high-quality data solutions.

 - Participate in code reviews and follow engineering best practices.


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