Data Engineer with hands on experience designing and implementing scalable data solutions. Specialized in building robust ETL/ELT pipelines, data warehousing, and cloud-based analytics infrastructure.
skills = {
"Languages": ["Python", "SQL", "Bash", "R"],
"Data Processing": ["Pandas", "NumPy", "PySpark", "Apache Spark", "Hadoop"],
"Orchestration": ["Airflow", "Cloud Composer"],
"Databases": ["BigQuery", "PostgreSQL", "MongoDB", "Apache Impala"],
"Data Modeling": ["dbt", "Data Warehousing", "Dimensional Modeling"],
"Cloud": ["GCP", "AWS", "Cloud Run", "Dataflow", "S3", "Lambda", "DynamoDB"],
"DevOps": ["Docker", "Git", "CI/CD", "Terraform"],
"Visualization": ["Tableau", "PowerBI", "Matplotlib", "Seaborn"]
}- Pipeline Development: Designing and maintaining robust data pipelines using Airflow, ensuring reliability and efficiency
- Data Warehouse Design: Creating scalable data models for analytics and reporting workloads
- Data Quality: Implementing comprehensive quality controls and monitoring systems
- Cloud Architecture: Building cloud-native data solutions on GCP and AWS
- Performance Optimization: Tuning database queries and ETL processes for maximum efficiency
- Designing event-driven data pipelines with real-time processing capabilities
- Implementing DataOps practices for improved collaboration between data teams
- Exploring modern data stack technologies and architectural patterns
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