Key accomplishments

1. Pioneered scalable data warehousing solutions at JP Morgan Chase, NY, leading to a 2x increase in data processing efficiency.
2. Optimized ETL pipelines using Python, Pandas, and Numpy, resulting in streamlined processing of large data volumes from various sources.
3. Applied advanced SQL querying techniques for data filtering, grouping, joining, and aggregation, ensuring high data quality and integrity.
4. Implemented cloud-based data processing pipelines on AWS and Azure, covering data ingestion, processing, transformation, and loading.
5. Orchestrated real-time stream processing pipelines using Apache Kafka and Spark Streaming, enabling efficient data ingestion and processing.
6. Designed data warehouses using Snowflake, supporting real-time analysis of large datasets and achieving optimal query performance.

Role 1
Data scientist
Role 2
Big Data Engineer/Architect
Test Score
AI, Machine learning, Data Science
100%
Data Engineer
100%
Financial technology > banking and exchange
full-time 40-hours-per-week
Any
Graduate
United States
Any
NA
Remote
Willing to work for paid projects

Tags

AITechFintechWealthtech

Education

Experience

Expertise

Data Engineer
95

Languages

English
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