
Data Engineering Expertise Wanted
3 days ago
We are seeking an experienced Data Engineering Professional to join our team.
The ideal candidate will have a strong background in designing and optimizing modern data platforms, with expertise in Databricks and Apache Spark. Key responsibilities include:
- Leading the architecture, development, and operations of large-scale data systems
- Designing and building efficient ETL/ELT pipelines using Python (PySpark)
- Setting up and maintaining continuous integration and continuous deployment (CI/CD) pipelines with Git/DevOps tools
- Crafting scalable data lakes, warehouses, and lakehouses to support business growth
- Optimizing Databricks clusters, jobs, and workflows for batch and streaming processing
To be successful in this role, you should have at least 5 years of experience in data engineering, with a proven track record of building and optimizing ETL pipelines using Azure Data Factory or similar tools.
You will also need to demonstrate solid understanding of CI/CD practices, Git integration, and automation for Databricks. Additionally, hands-on experience with Unity Catalog for governance, security, and lineage is highly desirable.
This is an excellent opportunity to work on cutting-edge projects and collaborate with a talented team of professionals who share your passion for data engineering.
Key Requirements:
- 5+ years of data engineering experience
- Strong expertise in Databricks & Apache Spark
- Hands-on experience with Unity Catalog for governance, security, and lineage
- Proven track record of building and optimizing ETL pipelines (Azure Data Factory, Informatica, etc.)
- Solid understanding of CI/CD practices, Git integration, and automation for Databricks
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