
Cloud Data Architectural Specialist
2 days ago
About the Opportunity
We are seeking a highly skilled Cloud Data Engineer to join our team. The ideal candidate will have experience in building data products using Databricks and related technologies.
This role involves managing existing cloud data platforms, ensuring they are scalable, reliable, and cost-efficient. Additionally, you will work on new projects that leverage existing architectures and utilize newer technologies where necessary.
Responsibilities:
- Analyze existing data warehouse implementations to support migration and consolidation efforts.
- Reverse-engineer legacy stored procedures (PL/SQL, SQL) and translate business logic into scalable Spark SQL code within Databricks notebooks.
- Design and develop data lake solutions on AWS using S3 and Delta Lake architecture, leveraging Databricks for processing and transformation.
- Build and maintain robust data pipelines using ETL tools with ingestion into S3 and processing in Databricks.
- Collaborate with data architects to implement ingestion and transformation frameworks aligned with enterprise standards.
- Evaluate and optimize data models (Star, Snowflake, Flattened) for performance and scalability in the new platform.
- Document ETL processes, data flows, and transformation logic to ensure transparency and maintainability.
- Perform foundational data administration tasks including job scheduling, error troubleshooting, performance tuning, and backup coordination.
- Work closely with cross-functional teams to ensure smooth transition and integration of data sources into the unified platform.
- Participate in Agile ceremonies and contribute to sprint planning, retrospectives, and backlog grooming.
- Triage, debug, and fix technical issues related to Data Lakes.
- Maintain and manage Code repositories like Git.
Requirements:
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, or related field.
- 5+ years of experience working with Databricks, including Spark SQL and Delta Lake implementations.
- 3+ years of experience in designing and implementing data lake architectures on Databricks.
- Strong SQL and PL/SQL skills with the ability to interpret and refactor legacy stored procedures.
- Hands-on experience with data modeling and warehouse design principles.
- Proficiency in at least one programming language (Python, Scala, Java).
- Experience working in Agile environments and contributing to iterative development cycles.
Preferred Skills:
- Databricks cloud certification is a big plus.
- Exposure to enterprise data governance and metadata management practices.
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