Description:
NXT GIG is looking for an experienced Azure Databricks Engineer to join our cutting-edge data team. In this role, you will be responsible for designing, developing, and optimizing data processing solutions using Azure Databricks and related Azure services. You will work closely with data scientists and analysts to create robust data pipelines, facilitate data ingestion, and ensure efficient data transformations. Your contributions will enable our organization to harness the power of big data and analytics effectively. If you are passionate about cloud-based data engineering and eager to make a significant impact using Azure technology, we invite you to apply to NXT GIG.
Responsibilities
- Design and implement data pipelines using Azure Databricks to support analytics and business intelligence needs.
- Collaborate with data scientists and other stakeholders to gather requirements and ensure seamless data integration.
- Optimize the performance of data processing workflows and troubleshoot issues as they arise.
- Develop and maintain data models and documentation for processing workflows and data architectures.
- Implement best practices for data governance, quality assurance, and security for data solutions.
- Stay current with Azure services and Databricks features to recommend enhancements and optimizations.
- Support the development of data-driven applications and reporting initiatives within the organization.
Requirements
- Bachelor's degree in Computer Science, Data Engineering, or a related field.
- Proven experience as an Azure Databricks Engineer or in a similar data engineering role.
- Strong knowledge of Azure services, including Azure Data Lake, Azure Synapse Analytics, and Azure Data Factory.
- Expertise in using Apache Spark, Databricks notebooks, and related technologies for big data processing.
- Proficiency in programming languages such as Python, Scala, or SQL.
- Experience with data modeling, ETL processes, and data warehousing concepts.
- Excellent analytical skills and the ability to work collaboratively in a team environment.
20 Mar 2025;
from:
uworkin.com