Data Engineer Self Service Analytics and Real Time Data Platforms
Tasks
- Build AI ready data products for machine learning and GenAI
- Build near real time streaming data pipelines
- Create semantic layers and metrics frameworks
- Design governed data access patterns for AI and conversational analytics
- Design scalable ETL/ELT pipelines
- Design scalable analytics and AI optimized data models
- Develop curated data products
- Enable governed self service business data models
- Ensure data quality governance metadata and discoverability
- Implement data monitoring and observability
- Implement real-time dashboards
- Integrate data pipelines with ML platforms
- Optimize complex SQL queries
Perks/Benefits
- 401k
- Dental insurance
- Disability benefits
- Life insurance
- Medical insurance
- Paid time off
- Tuition assistance
- Vision insurance
Skills/Tech-stack
Airflow | Apache Kafka | Cloud Pub/Sub | Cloud platform | Data Governance | Data Modeling | Data Pipelines | Data Quality | Data Warehouse | Databricks | Distributed Systems | ELT | ETL | Embeddings | Event Driven | Event-driven architecture | Feature Engineering | GCP | GenAI | Google Cloud | Google Cloud Platform | Google Cloud Pub/Sub | Kafka Streams | Lakehouse | Machine Learning | Metadata Management | Observability | Pub/Sub | Python | SQL | Spark | Streaming Data | Streaming data pipelines | Superset | Vector Databases | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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