
Data Platform Developer
2 days ago
Job Description:
As a Data Engineer, you will be responsible for designing and developing data pipelines, ETL processes, and workflows using Databricks.
The role involves supporting the current data environment, developing data ingestion pipelines, and monitoring data workflows. You will work closely with stakeholders to understand their requirements and provide data-driven solutions.
You will be working with large datasets and implementing data quality checks and monitoring to optimize data workflows and processes. Additionally, you will perform database testing and platform development work, ensuring that the data platforms are scalable and efficient.
Required Skills and Qualifications:
Extensive experience as an Azure Data Engineer is required, along with demonstrable hands-on experience in Azure Data services such as Azure Data Factory.
Strong experience building and supporting data platforms within an Azure Databricks environment is essential, as well as proficiency in programming languages such as Python, Scala, or Java.
A solid understanding of data warehousing concepts and ETL processes is also required, along with excellent stakeholder management skills.
Benefits:
As a Data Engineer at our organization, you will have the opportunity to work on challenging projects and develop your skills in a collaborative and supportive environment. You will be part of a team that values innovation and excellence, and you will have access to cutting-edge technology and tools.
Other Information:
This is a permanent position, working full-time hours, with a hybrid working arrangement. The ideal candidate will have strong communication and interpersonal skills, as well as the ability to work effectively in a team environment.
Key Responsibilities
Design and develop data pipelines, ETL processes, and workflows using Databricks.
Support the current data environment, develop data ingestion pipelines, and monitor data workflows.
Implement data quality checks and monitoring to optimize data workflows and processes.
Perform database testing and platform development work, ensuring that the data platforms are scalable and efficient.
Develop data processing & transformations (Azure Databricks) and design and develop data pipelines, ETL processes, and workflows using Databricks.
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