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2 weeks ago
Driven by innovation, we are seeking a seasoned Modern Data Solutions Architect to shape the future of data engineering. This pivotal role demands technical expertise, strategic vision, and leadership to deliver cutting-edge data solutions.
Key Responsibilities:- Design and lead advanced Databricks architectures, fostering scalability and performance.
- Develop and optimize ETL/ELT pipelines using Python (PySpark), ensuring seamless data flow.
- Implement and maintain CI/CD pipelines with Git/DevOps tools, streamlining development and deployment.
- Create and manage scalable data lakes, warehouses, and lakehouses, leveraging industry best practices.
- Optimize Databricks clusters, jobs, and workflows (batch and streaming) for maximum efficiency.
This is a full-time position with flexible shift timings. Our client is a leading AI-driven tech company transforming global enterprises with innovative solutions in data intelligence, automation, and responsible AI.
The ideal candidate will have 5+ years of data engineering experience, strong expertise in Databricks and Apache Spark, hands-on experience with Unity Catalog for governance, security, and lineage, and a proven track record of building and optimizing ETL pipelines. They should also have a solid understanding of CI/CD practices, Git integration, and automation for Databricks.
Requirements:- 5+ years of data engineering experience.
- Strong expertise in Databricks and Apache Spark.
- Hands-on experience with Unity Catalog for governance, security, and lineage.
- Proven track record of building and optimizing ETL pipelines.
- Solid understanding of CI/CD practices, Git integration, and automation for Databricks.
We seek a forward-thinking team member who can drive change with their ideas and leadership.
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