Data Engineer
Tasks
- Automate workflow orchestration
- Build and optimize ETL/ELT workflows
- Collaborate with analytics AI ML teams
- Design data lakes and data warehouses
- Design data pipelines for batch and streaming
- Develop data engineering solutions with Python
- Develop data ingestion frameworks
- Develop data models for analytics reporting and machine learning
- Implement CI/CD pipelines
- Implement event driven data processing
- Improve pipeline reliability scalability and performance
- Optimize pipeline performance and cost
- Troubleshoot data issues perform root cause analysis
Perks/Benefits
- Company-Paid Holidays
- Employee assistance program
- Life and disability insurance
- Medical, dental, and vision insurance
- Paid time off
- Retirement savings plan
Skills/Tech-stack
Apache Airflow | Bash/Shell | Bash/Shell Scripting | Batch Processing | Cloud Composer | Cloud Composer Airflow | Cloud Functions | Cloud Functions Gen2 | Cloud Monitoring | Cloud Run | Cloud SQL | Cloud Storage | Cloud logging | Cloud platform | Composer (Airflow) | Data Lake | Data Modeling | Data Warehousing | Dataflow | Dataproc | ELT | ETL | FinOps | GCP BigQuery | Gemini | Google Cloud | Google Cloud Platform | IAM | Infrastructure as Code | Lakehouse | Language Models | Large Language Models | Machine Learning | Metadata Modeling | Prompt engineering | Pub/Sub | PySpark | Python | RAG | SQL | Semantic Retrieval | Shell Scripting | Spark | Streaming Architecture | Terraform | Vector Search | Vertex AI | “as-code”
Education
N/A
Roles
Regions
Countries
States
Cities
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