As an Azure Data Engineer, design and optimize data pipelines using Databricks for large-scale data processes. Develop ETL workflows, implement Delta Lake for real-time data management, and collaborate with stakeholders to build scalable data solutions. Ensuring data integrity and leveraging MLflow for machine learning deployment are also key responsibilities.
Role : Azure Data Engineer
Exp : 4-7 yrs
Loc : Bangalore / Noida
Job Description :
Data Engineering with Databricks:
- Design, implement, and optimize data pipelines in Databricks to process large-scale structured and unstructured data.
- Develop ETL workflows for data ingestion, transformation, and integration using Databricks and other cloud-based tools.
- Implement Delta Lake for efficient data management and real-time data processing.
- Collaborate with data architects and stakeholders to build scalable and reusable data solutions.
- Leverage Databricks' MLflow for managing and deploying machine learning workflows, if required.
- Ensure data quality, integrity, and compliance with organizational standards and governance policies.
Required Skills & Qualifications:
- Education: Bachelor’s or master’s degree in computer science, Data Analytics, Information Technology, or a related field.
- Technical Proficiency:
- Hands-on experience with Databricks: Spark, Pyspark, Scala, or SQL.
- Strong understanding of database concepts and working experience with SQL/NoSQL databases.
- Experience integrating Databricks and Power BI with cloud platforms like Azure or AWS.
- Analytical Skills: Strong ability to analyse, interpret, and visualize large datasets.
- Problem Solving: Demonstrated ability to troubleshoot complex data workflows and reporting challenges.
Soft Skills: Strong written and verbal communication, collaboration, and stakeholder management
Top Skills
Pyspark
Scala
Spark
SQL
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