Summary

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. This role requires deep technical expertise, a passion for working with data, and strong analytical skills.

Key Responsibilities

Data Infrastructure Development:

1. Design, develop, and maintain scalable data pipelines to collect, process, and store large volumes of structured and unstructured data.
2. Implement data integration solutions to consolidate data from various sources, ensuring data quality and integrity.
3. Optimize data storage and retrieval processes for performance and scalability.

Analytics and Reporting:

1. Develop and maintain data models, dashboards, and reports to support business analytics and decision-making.
2. Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and provide robust solutions.
3. Conduct exploratory data analysis to discover trends, patterns, and insights that drive business strategy.

Data Quality and Governance:

1. Implement data validation and monitoring processes to ensure data accuracy and consistency.
2. Establish and enforce data governance policies and best practices.
3. Conduct regular audits and data quality assessments to identify and resolve data issues.

Collaboration and Communication:

1. Work closely with cross-functional teams, including product, engineering, and business teams, to understand data requirements and deliver solutions that meet business needs.
2. Communicate complex data insights and technical details to non-technical stakeholders effectively.
3. Provide technical guidance and mentorship to junior data engineers and analysts.

Continuous Improvement:

1. Stay current with the latest trends and technologies in data engineering and analytics.
2. Continuously evaluate and implement new tools and technologies to improve data processing, analysis, and visualization capabilities.
3. Drive the adoption of best practices in data engineering and analytics across the organization.

Qualifications

1. Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field.
2. 5+ years of experience in data engineering, data analytics, or a related field.
3. Strong proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL).
4. Experience with big data technologies (e.g., Hadoop, Spark) and data warehousing solutions (e.g., BigQuery, Snowflake).
5. Proficiency in programming languages such as Python or Scala.
6. Experience with data visualization tools (e.g., Tableau, Power BI, Looker).
7. Strong understanding of ETL processes, data modeling, and data warehousing concepts.
8. Excellent problem-solving skills and attention to detail.
9. Strong communication and interpersonal skills, with the ability to work effectively in a collaborative environment.

Preferred Qualifications

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

Minimum full-time salary of $196,000- $217,000. Disclosure in accordance with New York City's Pay Transparency Law. Full Time employees at Uniswap Labs are also eligible for other compensation elements, including equity, tokens, and benefits, dependent on the position type.

Skills

• Attention to Detail
• Communications Skills
• Database Management
• Development
• Problem Solving
• Software Engineering
• SQL
• Team Collaboration