AI Data Engineer
Tasks
- Align data pipelines with model development and deployment needs
- Build and maintain data ingestion frameworks
- Create and manage feature stores
- Design and implement distributed data pipelines for batch processing
- Design and implement distributed data pipelines for real time processing
- Develop and optimize data models and warehouse schemas
- Enforce data governance, security, and compliance
- Ensure real time data availability for AI and analytics
- Implement data monitoring systems
- Implement data quality validation frameworks
- Integrate data from multiple internal and external sources
- Optimize data pipeline performance
Perks/Benefits
- Career progression
- Collaborative culture
- Continuous learning
- Innovation-focused culture
- International organization
- Ownership culture
- Performance-Based Incentives
Skills/Tech-stack
AWS Glue | AWS Lambda | Amazon EMR | Amazon Kinesis | Amazon Redshift | Amazon S3 | Apache Airflow | Apache Spark | DBT | Data Governance | Data Lineage | Data Modeling | Data Monitoring | Data Processing | Data Quality | Dimensional Modeling | ELT | ETL | Feature Engineering | Google BigQuery | Hadoop | Kafka | Machine Learning | Normalization | Python | Real Time | Real-time Data | Real-time Data Processing | SQL | Snowflake | Star Schema
Education
N/A
Roles
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