Senior Data Engineer
oraclecloud
Job Description
- Architect and implement a modern data platform leveraging medallion architecture (Raw, Silver, Gold layers) on Snowflake and DBT
- Develop and manage batch ingestion pipelines using AWS Glue and real-time streaming pipelines using Amazon Kinesis
- Design scalable data models and transformation logic using DBT to support enterprise analytics and reporting needs
- Lead data pipeline optimization initiatives focusing on performance, scalability, and cost efficiency
- Ensure data quality, consistency, and governance through validation frameworks and monitoring mechanisms
- Support report rationalization initiatives by streamlining data layers and reducing redundancy
- Collaborate with cross-functional teams to translate business requirements into robust data engineering solutions
Core Skills & Expertise
- Strong hands-on experience with:
- Snowflake (data warehousing, performance tuning)
- DBT (data transformation, modelling, testing)
- AWS Glue (batch ETL pipelines)
- Amazon Kinesis (real-time data streaming)
- Advanced proficiency in SQL and data modelling (dimensional and normalized)
- Experience implementing Raw/Silver/Gold data architectures
- Strong programming skills in Python/Scala
- Expertise in pipeline performance tuning and cost optimization
- Insurance domain background preferred
Experience
- 6–10+ years in Data Engineering / Data Platform Development
- Proven experience building large-scale, cloud-based data platforms
Success Measures
- High-performing, scalable, and reliable data pipelines
- Reduced data latency across batch and real-time workloads
- Improved data quality and governance standards
- Measurable cost and performance optimization in data platform operations