Senior Data Engineer, Uniswap Labs

• This role requires deep technical expertise, a passion for working with data, and strong analytical skills
• Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field
• 5+ years of experience in data engineering, data analytics, or a related field
• Strong proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL)
• Experience with big data technologies (e.g., Hadoop, Spark) and data warehousing solutions (e.g., BigQuery, Snowflake)
• Proficiency in programming languages such as Python or Scala
• Experience with data visualization tools (e.g., Tableau, Power BI, Looker)
• Strong understanding of ETL processes, data modeling, and data warehousing concepts
• Excellent problem-solving skills and attention to detail
• Strong communication and interpersonal skills, with the ability to work effectively in a collaborative environment

Desirable

• We are seeking a highly skilled and experienced Senior Data Analytics Engineer to join our dynamic data engineering team
• The ideal candidate will be responsible for designing, implementing, and optimizing our data analytics infrastructure to support our data-driven decision-making processes
• Data Infrastructure Development:
• Design, develop, and maintain scalable data pipelines to collect, process, and store large volumes of structured and unstructured data
• Implement data integration solutions to consolidate data from various sources, ensuring data quality and integrity
• Optimize data storage and retrieval processes for performance and scalability
• Analytics and Reporting:
• Develop and maintain data models, dashboards, and reports to support business analytics and decision-making
• Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and provide robust solutions
• Conduct exploratory data analysis to discover trends, patterns, and insights that drive business strategy
• Data Quality and Governance:
• Implement data validation and monitoring processes to ensure data accuracy and consistency
• Establish and enforce data governance policies and best practices
• Conduct regular audits and data quality assessments to identify and resolve data issues
• Collaboration and Communication:
• Work closely with cross-functional teams, including product, engineering, and business teams, to understand data requirements and deliver solutions that meet business needs
• Communicate complex data insights and technical details to non-technical stakeholders effectively
• Provide technical guidance and mentorship to junior data engineers and analysts
• Continuous Improvement:
• Stay current with the latest trends and technologies in data engineering and analytics
• Continuously evaluate and implement new tools and technologies to improve data processing, analysis, and visualization capabilities
• Drive the adoption of best practices in data engineering and analytics across the organization