Leading Azure Data Solutions

5 days ago

Pune, Maharashtra, India beBeeDataEngineer Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

We are looking for a skilled Azure data engineer to create and manage scalable, reliable data pipelines and solutions on the Microsoft Azure platform.

Key Responsibilities:

  • Create robust data pipelines and ETL/ELT workflows using Azure Data Factory and related tools.
  • Develop and optimize data models in Azure Synapse Analytics, Azure SQL Database, and Azure Data Lake.
  • Integrate data from multiple sources including structured, semi-structured, and unstructured datasets.
  • Develop scalable data ingestion processes and automate data movement across environments.
  • Implement data quality, data governance, and security best practices.
  • Collaborate with data scientists, analysts, and business stakeholders to meet reporting and analytics requirements.
  • Monitor data pipeline performance and troubleshoot issues proactively.
  • Optimize and refactor legacy data processes for better performance and cost efficiency on Azure.

Required Skills and Experience:

  • 7-9 years of experience as a Data Engineer, with at least 2 years working on Azure Data Services.
  • Proficiency in Azure Data Factory, Azure Data Lake, Azure SQL, Azure Synapse Analytics, and Azure Databricks.
  • Strong SQL skills and experience with stored procedures, views, and performance tuning.
  • Experience in data modeling and designing star/snowflake schemas for data warehouses.
  • Hands-on experience with Spark, PySpark, or Dataflows in Databricks.
  • Familiarity with CI/CD for data pipelines using tools like Azure DevOps.
  • Knowledge of data governance, data quality, and security principles in a cloud environment.

Benefits and Opportunities:

  • Pursue professional development through certification programs such as Microsoft Certified: Azure Data Engineer Associate (DP-203).
  • Gain hands-on experience with Power BI integration and data visualization best practices.
  • Explore big data technologies and work with large-scale data environments.
  • Enhance programming skills with languages like Python or Scala.
  • Contribute to modern data architectures like Data Lakehouse or Delta Lake.

Towards Success:

  • Establish strong collaboration with data scientists and analysts to deliver actionable insights.
  • Cultivate expertise in data security, compliance, and risk management.
  • Continuously improve data quality, integrity, and accuracy.
  • Invest in staying up-to-date with industry trends and innovations.

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