Summary

You will be at the intersection of data engineering and analytics, transforming data into meaningful insights that deepen the understanding of the business landscape and drive key decisions. You will work closely with data analysts, business analysts, and cross-functional teams to design scalable data models, optimize queries, and develop robust data pipelines that support analytical workloads.

Responsibilities

1. Design, implement, and optimize data pipelines and data models to support reporting, dashboards, and advanced analytics in the BigQuery ecosystem, GCP
2. Optimize SQL queries and data processing logic for performance and cost-efficiency
3. Contribute to data governance, documentation, and best practices for analytics engineering
4. Ensure data quality by applying strong data debugging skills and attention to detail
5. Adapt to a fast-paced, evolving environment with ambiguous requirements
6. Work closely with various global cross-functional teams, applying strong communication and technical expertise to resolve technical challenges.

Qualifications

1. Bachelor's degree in Computer Science or a related field
2. 2-7 years of professional experience
3. Strong proficiency in SQL and experience with data modeling for analytics
4. Strong problem-solving skills, ability to learn quickly, and adapt
5. Strong desire to improve on inefficient processes
6. Positive attitude and ability to receive and provide objective and constructive feedback
7. Cultivate strong partnerships with cross-functional stakeholders
8. Capable of participating in meetings and discussions in both Korean and English

Preferred

1. Hands-on industry experience in software development
2. Self-driven, proactive personality, and critical thinking
3. Experience in a cryptocurrency exchange or fintech company
4. Experience working with web-scale datasets.
5. Experience in distributed computing
6. Experience in Cloud/Big Data Platforms (e.g., AWS, GCP, Beam, Spark, etc.)

Skills

• AWS
• Critical Thinking
• Cryptocurrency
• Database Management
• Development
• Software Engineering
• SQL