| name | senior-data-engineer |
| description | World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, or implementing data governance. |
Senior Data Engineer
World-class senior data engineer skill for production-grade AI/ML/Data systems.
Quick Start
Main Capabilities
python scripts/pipeline_orchestrator.py --input data/ --output results/
python scripts/data_quality_validator.py --target project/ --analyze
python scripts/etl_performance_optimizer.py --config config.yaml --deploy
Core Expertise
This skill covers world-class capabilities in:
- Advanced production patterns and architectures
- Scalable system design and implementation
- Performance optimization at scale
- MLOps and DataOps best practices
- Real-time processing and inference
- Distributed computing frameworks
- Model deployment and monitoring
- Security and compliance
- Cost optimization
- Team leadership and mentoring
Tech Stack
Languages: Python, SQL, R, Scala, Go
ML Frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost
Data Tools: Spark, Airflow, dbt, Kafka, Databricks
LLM Frameworks: LangChain, LlamaIndex, DSPy
Deployment: Docker, Kubernetes, AWS/GCP/Azure
Monitoring: MLflow, Weights & Biases, Prometheus
Databases: PostgreSQL, BigQuery, Snowflake, Pinecone