Data Engineer

What we're looking for

• Architect and lead the development of robust and scalable data collection infrastructure, covering various protocols.
• Oversee the collection, research, and analysis of operational and blockchain data.
• Drive initiatives to enhance data system performance and reliability, Innovate and optimize internal data practices, addressing gaps and inefficiencies.
• Ensure impeccable data accuracy and completeness during transfer and loading into enterprise repositories.
• Spearhead the establishment and maintenance of security and integrity controls.
• Formulate and monitor data warehouse management policies, procedures, and standards.
• Lead cross-functional project teams in analyzing business requirements, conducting complex data analysis, and supporting user acceptance testing for diverse data needs.
• Expertly organize and interpret data trends, uncovering patterns and insights.
• Collaborate closely with crypto product managers, business analysts, and engineers to fulfill data requirements.
• Develop advanced scripts to automate complex accounting and data processes.
• Lead scripting and scraping projects for data modeling preparation.
• Optimize and refine data architecture for seamless retrieval.
• Enhance data resiliency, redundancy, and recovery mechanisms.
• Develop cutting-edge tools for identifying and documenting public data sources.
• Analyze and interpret operational data from various infrastructure systems, collaborating closely with the Infrastructure Team.
• Spearhead the design and management of comprehensive data lakes and data marts for infrastructure data.
• Develop and implement advanced data solutions while driving infrastructure information gathering initiatives.

• Bachelor's degree in computer science, data engineering, information technology, or a related field.
• 5+ years of hands-on experience in data engineering, with a track record of delivering complex data solutions, or equivalent experience.
• Expertise in programming languages such as Python, Java, or Scala. Python preferred.
• Deep knowledge of database systems (SQL, NoSQL) and advanced data modeling concepts.
• Proficiency in big data technologies (e.g., Hadoop, Spark, Kafka) and distributed computing.
• Strong experience with cloud platforms (AWS preferred) and containerization technologies (Docker preferred).
• Strong experience working with Snowflake data warehouse.
• Strong experience with data transformation tools like dbt (data build tool).
• Strong proficiency in job scheduling and orchestration tools such as Prefect, Dagster, or Airflow.
• Familiarity with data integration tools like Fivetran, Stitch, Hevo, Airbyte.
• Experience with Terraform for managing data infrastructure.
• Excellent problem-solving skills, attention to detail, and ability to lead technical projects.
• Effective communication and collaboration skills, with the ability to work across cross-functional teams.

• Certifications in AWS Certified Data Analytics, Google Cloud Professional Data Engineer, or Microsoft Certified
• Experience with advanced data warehousing solutions like Amazon Redshift, Google BigQuery, or Snowflake, as well as expertise in data warehousing best practices
• Familiarity with machine learning and artificial intelligence concepts and tools
• Expertise in data governance frameworks and data compliance regulations, such as GDPR or HIPAA
• Proficiency in DevOps practices, continuous integration, and continuous deployment (CI/CD) pipelines
• Prior experience working in a startup environment, with an understanding of the fast-paced and dynamic nature of startups
• Experience working with global teams