Cloud Data Platform Specialist
11 hours ago
We're seeking a skilled Cloud Data Engineer to join our team and drive the growth of our advanced analytics practice. This is an exciting opportunity to build and scale our cloud data platform, making it more scalable, reliable, and cost-efficient.
The ideal candidate will have experience with Databricks, including Spark SQL and Delta Lake implementations. They should be proficient in at least one programming language (Python, Scala, Java) and have hands-on experience with data modeling and warehouse design principles.
Responsibilities:
- Analyze existing data warehouse implementations for migration and consolidation.
- Reverse-engineer legacy stored procedures and translate business logic into scalable Spark SQL code in 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.
Qualifications:
- 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.
- 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.
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