Manager, Azure Data Engineer

Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

Responsibilities: 

• Design, develop, and optimize data pipelines and ETL processes using PySpark or Scala to extract, transform, and load large volumes of structured and unstructured data from diverse sources. 

• Implement data ingestion, processing, and storage solutions on Azure cloud platform, leveraging services such as Azure Databricks, Azure Data Lake Storage, and Azure Synapse Analytics. 

• Develop and maintain data models, schemas, and metadata to support efficient data access, query performance, and analytics requirements. 

• Monitor pipeline performance, troubleshoot issues, and optimize data processing workflows for scalability, reliability, and cost-effectiveness. 

• Implement data security and compliance measures to protect sensitive information and ensure regulatory compliance. 

• Requirement 

• Proven experience as a Data Engineer, with expertise in building and optimizing data pipelines using PySpark, Scala, and Apache Spark. 

• Hands-on experience with cloud platforms, particularly Azure, and proficiency in Azure services such as Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database. 

• Strong programming skills in Python and Scala, with experience in software development, version control, and CI/CD practices. 

• Familiarity with data warehousing concepts, dimensional modeling, and relational databases (e.g., SQL Server, PostgreSQL, MySQL). 

• Experience with big data technologies and frameworks (e.g., Hadoop, Hive, HBase) is a plus. 

Mandatory skill sets: 

Spark, Pyspark, Azure 

Preferred skill sets: 

Spark, Pyspark, Azure 

Years of experience required: 

8 - 12

Education qualification: 

B.Tech / M.Tech / MBA / MCA