Data Engineer
7 dni temu
We are looking for candidates with few years of experience (regular level) as well with more experience (senior level).
Responsibilities:
• Design & Develop: Collaborate with the team to build scalable data platforms on Azure Cloud , leveraging Azure Data Factory, Databricks, ADLS, and other Azure services .
• Data Management: Integrate diverse data sources, ensuring data quality, consistency, and governance . Implement security measures using Azure Purview, Key Vault, and Databricks Unity Catalog for access control and auditing.
• Collaboration: Work closely with data scientists and analysts to deliver efficient data solutions. Support and maintain the data platform, leveraging Azure Monitor and Log Analytics for
troubleshooting.
• Code Management & Optimization: Develop and maintain production-grade data pipelines using Spark & PySpark , ensuring version control in Git and following best practices for CI/CD .
• Continuous Improvement: Stay up to date with Azure and Databricks technologies to optimize workflows and automate processes for efficiency.
Qualifications:
• Education: Bachelor’s in Computer Science or a related field (Master’s is a plus).
• Experience: Proven experience working with Azure Cloud data platforms , including Data Factory, Databricks, ADLS, SQL Databases, and Spark/PySpark .
• Technical Skills:
• Strong experience in Spark & PySpark for big data processing.
• Proficiency in Python, Scala, or Java for data engineering tasks.
• Knowledge of SQL/NoSQL databases, ETL, and data warehousing principles .
• Strong understanding of Git for version control and CI/CD processes in a data engineering environment.
• Soft Skills: Strong communication, problem-solving skills , and the ability to collaborate effectively across teams.
Additional Technologies in the Project:
• The project will also involve Databricks Asset Bundles (DAB) and Delta Live Tables (DLT) for managing and deploying data pipelines.
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