Senior Data Engineer

Summary

Join Uniswap Labs as a Senior Data Analytics Engineer and contribute to the development and optimization of our data analytics infrastructure. You will design, implement, and maintain scalable data pipelines, develop data models and reports, and ensure data quality and governance. Collaboration with cross-functional teams is crucial, as is staying current with the latest technologies. This role requires a Bachelor's or Master's degree, 5+ years of experience, and strong proficiency in SQL and big data technologies. The ideal candidate will possess excellent problem-solving and communication skills. Uniswap Labs offers a competitive salary, comprehensive benefits, and a dynamic work environment.

Requirements

• 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

Responsibilities

• 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
• 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
• 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
• 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
• 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

Preferred Qualifications

• Experience with cloud data platforms (e.g., AWS, GCP, Azure)
• Knowledge of machine learning and data science techniques
• Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink)
• Relevant certifications in data engineering or analytics

Benefits

• Company-paid medical, dental, & vision for you and your dependents
• Gym subsidy
• 401(k) with 4% employer contribution
• Annual $1,500 education stipend
• Unlimited and encouraged time off
• Up to 16 weeks paid parental leave
• Home office setup stipend for remote employees
• Daily lunches at NY headquarters