Data Engineer
1. Data Pipeline
- Develop and optimize ETL/ELT pipelines using modern data tools and frameworks
- Write efficient code in Python and SQL for data transformation and processing
- Implement data validation and testing frameworks
- Create automated workflows for data processing and monitoring
- Troubleshoot and resolve data pipeline issues
2. Data Warehousing
- Design and maintain enterprise data warehouse architecture
- Implement dimensional modeling and data mart solutions
- Optimize query performance and data access patterns
- Develop data documentation and lineage tracking
- Create and maintain data schemas and models
- Implement data governance and quality control mechanisms
- 5+ years of experience in data engineering.
- Bachelor's degree or higher in Computer Science, Data Engineering, or a related field.
- Advanced SQL and Python programming skills, including optimization and performance tuning.
- Strong proficiency in cloud platforms (GCP, AliCloud, AWS).
- Expertise in big data technologies (Spark, Flink, Presto, StarRocks, Data Lake, Airflow).
- Solid understanding of data warehousing concepts and best practices.
- Experience with BI tools (Tableau, Looker, Datawind).
- Knowledge of data quality frameworks and tools.
- Strong problem-solving, analytical, and communication skills.
- Ability to work independently and collaboratively in a fast-paced environment.
- Experience in the financial services or fintech industry, particularly within the crypto/blockchain space, is a strong plus.
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