Compunnel
We are seeking a skilled Data Engineer proficient in Python, SQL, and Azure Databricks to design, develop, and maintain scalable data pipelines and ETL processes.
The ideal candidate will work closely with cross-functional teams to ensure high-quality, efficient data integration and transformation solutions within a cloud environment.
This role demands strong problem-solving skills, a solid understanding of data governance, and hands-on experience with Azure cloud services.
Key Responsibilities:
Design, develop, and maintain scalable data pipelines and ETL processes using Azure Databricks, Data Factory, and other Azure services.
Implement and optimize Spark jobs, data transformations, and workflows within Databricks.
Develop and maintain data models and data dictionaries using Python and SQL.
Develop and maintain data quality checks, governance policies, and security procedures.
Design and create ETL processes to supply data to various destinations, including data warehouses.
Integrate data from various sources into Azure Databricks.
Collaborate with data engineers, data scientists, and analysts to ensure data quality and consistency.
Implement monitoring processes to track performance and optimize workflows.
Contribute to the design and implementation of data lakehouse solutions using Databricks.
Required Qualifications:
Proficiency with Azure Databricks, including PySpark and Spark. Strong programming skills in Python, SQL, and Scala. Solid understanding of ETL processes, data warehousing concepts, and data modeling. Experience working with cloud platforms, particularly Microsoft Azure. Proven experience in data engineering, including data pipelines and data integration. Knowledge of data governance policies and procedures. Excellent problem-solving and debugging skills. Strong communication and teamwork skills. Preferred Qualifications:
Experience with Azure Data Factory and other Azure analytics services. Familiarity with DevOps tools and CI/CD pipelines for data workflows. Exposure to big data technologies such as Hadoop or Kafka. Experience with containerization tools like Docker and orchestration with Kubernetes. Knowledge of machine learning pipelines and integration with data engineering workflows. Prior experience working in Agile or Scrum environments. Email ID * This field is required Please enter valid emailId.
Cell phone * This field is required Please enter valid cell phone. First Name * This field is required Please enter valid first name. Last Name * This field is required Please enter valid last name. #J-18808-Ljbffr
Proficiency with Azure Databricks, including PySpark and Spark. Strong programming skills in Python, SQL, and Scala. Solid understanding of ETL processes, data warehousing concepts, and data modeling. Experience working with cloud platforms, particularly Microsoft Azure. Proven experience in data engineering, including data pipelines and data integration. Knowledge of data governance policies and procedures. Excellent problem-solving and debugging skills. Strong communication and teamwork skills. Preferred Qualifications:
Experience with Azure Data Factory and other Azure analytics services. Familiarity with DevOps tools and CI/CD pipelines for data workflows. Exposure to big data technologies such as Hadoop or Kafka. Experience with containerization tools like Docker and orchestration with Kubernetes. Knowledge of machine learning pipelines and integration with data engineering workflows. Prior experience working in Agile or Scrum environments. Email ID * This field is required Please enter valid emailId.
Cell phone * This field is required Please enter valid cell phone. First Name * This field is required Please enter valid first name. Last Name * This field is required Please enter valid last name. #J-18808-Ljbffr