Data Leader

Responsibilities

Lead team recruitment, training, performance management and echelon building; establish technical standards and work norms to build a high-efficiency collaborative data team.

Plan and build core data infrastructure (data warehouse, data lake, real-time data platform) and design business-adaptive data models/layered architectures for unified integration of multi-source data (trading, payment, user, operation, etc.).

Build and implement enterprise-level data governance systems (data quality, security, caliber, lifecycle management) to eliminate data silos and ensure data accuracy, integrity and reusability.

Lead the selection, construction and optimization of data platforms/tools (Databricks, AWS, Spark, Kafka, etc.); promote the best practices of big data and cloud native technologies to improve data development efficiency.

Deeply connect with cross-departmental business needs (trading, payment, compliance, operation); provide customized data analysis, dashboards and API support to empower data-driven business growth and risk control.

Oversee the whole lifecycle of key data projects (platform upgrade, data integration, governance implementation); control project progress, quality and cost to ensure on-time delivery and business goals achievement.

Track the latest trends in big data, data governance and cloud technologies; introduce industry best practices to continuously optimize the company’s data system and enhance technical competitiveness.

Requirements

Bachelor’s/Master’s degree in Computer Science, Software Engineering, Data Science or related fields; 8+ years of data industry experience, 3+ years of data team management experience ; crypto/fintech/payments industry experience is a MUST.

Proficiency in big data tech stack: Apache Spark/Flink/Kafka (real-time/offline data processing), Databricks/Delta Lake; hands-on experience in data warehouse/lake architecture design and implementation.

Expertise in AWS cloud services (EC2, S3, Glue, EMR, Redshift); with cloud-native data architecture design and operation capabilities.

Mastery of data modeling methodologies (dimensional modeling, star/snowflake schema); rich experience in financial/trading data modeling for high-concurrency, large-volume business scenarios.

Solid programming skills in Python/Scala/Java ; proficient in ETL development process, able to lead the design and optimization of complex data pipelines.

Proven experience in building and implementing enterprise-level data governance systems; able to solve practical data governance problems (quality, security, caliber unification).

Excellent team leadership and project management capabilities; strong business acumen to translate business needs into data solutions.

Outstanding cross-departmental communication and collaboration skills; able to work efficiently with technical, business and compliance teams.

Fluent in English (written & spoken) ; able to work in an English-speaking environment.

Preferred Qualifications

AWS/Azure/GCP cloud certification (e.g., AWS Data Analytics Specialty).

Experience in building data middle platforms and enterprise-level data assetization.

Familiar with financial/crypto data compliance requirements (GDPR, local financial regulations).

Hands-on experience with DevOps/Infra-as-Code tools (Terraform) and BI tools (Metabase).