Senior Cloud Architect
3 days ago
We are seeking an experienced data modeler to join our team. The ideal candidate will bring deep expertise in designing scalable and efficient data models for cloud platforms, particularly with a strong background in Oracle Data Warehousing and Databricks Lakehouse architecture.
- Job Responsibilities:
- Design and implement conceptual, logical, and physical data models that support business requirements and analytics needs.
- Lead the migration of data models from an on-prem Oracle Data Warehouse to Databricks on AWS or Azure cloud.
- Reverse-engineer and analyze complex Oracle schemas, PL/SQL code, and existing structures to build equivalent or improved models on the cloud.
- Collaborate with data architects and engineers to define optimal data structures in Databricks, leveraging Delta Lake and Spark.
- Optimize data models for performance, scalability, and cost-efficiency in a cloud-native environment.
- Develop and maintain dimensional models using star and snowflake schemas to support BI and reporting tools.
- Ensure data governance standards are met by incorporating metadata management, data lineage, and documentation practices.
- Participate in data architecture reviews and provide input on best practices in modeling and data pipeline integration.
- 5+ years of hands-on experience in data modeling, including conceptual, logical, and physical design.
- Proven experience migrating large-scale Oracle DWH environments to Databricks Lakehouse or similar platforms.
- Strong expertise in Oracle database schemas, PL/SQL, and performance tuning.
- Proficiency in Databricks, Delta Lake, Spark SQL, and DataFrame APIs.
- Experience designing models optimized for cloud platforms (preferably AWS or Azure).
- Deep knowledge of dimensional modeling techniques (Star/Snowflake).
- Familiarity with tools and practices for metadata management, data lineage, and governance.
- Strong analytical and communication skills with the ability to work collaboratively in Agile teams.
- Ability to document and communicate data model designs to both technical and non-technical stakeholders.
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