Azure Data Engineer at Enable Data Incorporated

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

03 May, 26

Salary

0.0

Posted On

02 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure Data Engineer, Microsoft Azure, Data Ingestion Pipelines, Data Integration, Data Transformation, Data Storage, Data Retrieval, Data Quality, Data Governance, Azure SQL Database, Azure Data Lake, Azure Blob Storage, Apache Spark, Azure Databricks, Python, SQL

Industry

IT Services and IT Consulting

Description

Enable Data Incorporated is currently seeking a skilled and experienced Azure Data Engineer to join our dynamic team. As a leading provider of advanced application, data, and cloud engineering services, Enable Data has developed deep expertise across various industries. We work closely with our customers to leverage modern solutions and technologies to drive increased value across their business ecosystem. As an Azure Data Engineer, you will play a crucial role in designing, building, and maintaining scalable and reliable data solutions on the Microsoft Azure platform. You will work closely with cross-functional teams to understand data requirements, design and implement data ingestion pipelines, perform data integration and transformation, and implement data storage and retrieval mechanisms. You will also be responsible for monitoring data pipelines and implementing data quality and governance measures. This is an exciting opportunity for a talented Data Engineer who is passionate about working with Azure technologies and wants to contribute to the success of our clients. If you have strong technical skills, a deep understanding of data engineering principles, and hands-on experience with Microsoft Azure, we would love to hear from you. Responsibilities Design, develop, and implement scalable and reliable data solutions on the Microsoft Azure platform. Collaborate with cross-functional teams to gather and analyze data requirements. Design and implement data ingestion pipelines to collect data from various sources, ensuring data integrity and reliability. Perform data integration and transformation activities, ensuring data quality and consistency. Implement data storage and retrieval mechanisms, utilizing Azure services such as Azure SQL Database, Azure Data Lake, and Azure Blob Storage. Monitor data pipelines and troubleshoot issues to ensure smooth data flow and availability. Implement data quality measures and data governance practices to ensure data accuracy, consistency, and privacy. Collaborate with data scientists and analysts to support their data needs and enable data-driven insights. Bachelor's degree in Computer Science, Engineering, or a related field. 5+ years of experience with Big Data technologies Strong knowledge and experience with Microsoft Azure cloud platform Proficiency in SQL and experience with SQL-based database systems. Experience with batch and data streaming. Proficiency in data processing frameworks such as Apache Spark, Apache Hadoop, or cloud-native data processing services (Azure Data Lake, Azure Data factory, Azure Databricks, Azure Synapse, Snowflake, CosmosDB) Hands-on experience with Azure data services, such as Azure SQL Database, Azure Data Lake, and Azure Blob Storage. Experience using Azure Databricks in real-world scenarios. Experience with data integration and ETL (Extract, Transform, Load) processes. Strong analytical and problem-solving skills. Good understanding of data engineering principles and best practices. Experience with programming languages such as Python or Scala. Relevant certifications in Azure data services or data engineering are a plus.

Responsibilities

The Azure Data Engineer will design, build, and maintain scalable and reliable data solutions on the Microsoft Azure platform, including designing and implementing data ingestion pipelines and performing data integration and transformation activities. Responsibilities also include monitoring data pipelines and implementing data quality and governance measures to ensure data accuracy and consistency.