Senior Data Engineer (Perp DEX)
Summary
Build and maintain scalable data pipelines and ETL processes for a decentralized exchange, using Snowflake, Airflow, dbt, and AWS.
We are representing a leading force in the decentralized exchange (DEX). We are seeking a seasoned Data Engineer to spearhead the development of robust data architectures. In this role, you will be responsible for the end-to-end lifecycle of data, from ingestion to insight, ensuring our infrastructure is both high-performing and scalable to meet the demands of a fast-paced business environment.
Key Responsibilities
Design & Architecture: Architect, build, and maintain scalable data pipelines and sophisticated ETL processes to support complex data ecosystems. Infrastructure Optimization: Enhance data warehouse performance and implement rigorous data quality frameworks to ensure 'single source of truth' reliability. Strategic Partnership: Collaborate closely with Product, Engineering, and Go-to-Market teams to translate business requirements into actionable data solutions. Operational Excellence: Develop automated monitoring systems to proactively identify and resolve pipeline bottlenecks. Agile Response: Execute high-priority, ad-hoc data requests and critical analyses with speed and precision to support urgent stakeholder decision-making.
Required Qualifications & Skills
Professional Experience: Minimum of 7+ years in dedicated Data Engineering roles, ideally within a high-growth environment. Advanced Data Modeling: Deep expertise in data architecture, warehouse design (e.g., Star/Snowflake schemas), and modern ETL/ELT best practices. Technical Stack: Mastery of the modern data stack, including Snowflake, Airflow, and dbt. Cloud & Infrastructure: Strong proficiency with AWS services and experience managing distributed systems. Stream Processing: Hands-on experience with data streaming technologies such as Kafka or Kinesis to optimize large-scale workflows. Problem Solving: A proven ability to navigate ambiguity and deliver high-quality solutions under tight deadlines.
Key Responsibilities
Design & Architecture: Architect, build, and maintain scalable data pipelines and sophisticated ETL processes to support complex data ecosystems. Infrastructure Optimization: Enhance data warehouse performance and implement rigorous data quality frameworks to ensure 'single source of truth' reliability. Strategic Partnership: Collaborate closely with Product, Engineering, and Go-to-Market teams to translate business requirements into actionable data solutions. Operational Excellence: Develop automated monitoring systems to proactively identify and resolve pipeline bottlenecks. Agile Response: Execute high-priority, ad-hoc data requests and critical analyses with speed and precision to support urgent stakeholder decision-making.
Required Qualifications & Skills
Professional Experience: Minimum of 7+ years in dedicated Data Engineering roles, ideally within a high-growth environment. Advanced Data Modeling: Deep expertise in data architecture, warehouse design (e.g., Star/Snowflake schemas), and modern ETL/ELT best practices. Technical Stack: Mastery of the modern data stack, including Snowflake, Airflow, and dbt. Cloud & Infrastructure: Strong proficiency with AWS services and experience managing distributed systems. Stream Processing: Hands-on experience with data streaming technologies such as Kafka or Kinesis to optimize large-scale workflows. Problem Solving: A proven ability to navigate ambiguity and deliver high-quality solutions under tight deadlines.