Informacje o stanowisku

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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