Senior Data Engineer

• Provide senior-level contribution to a team responsible for the architecture, design, deployment, and maintenance of the company's business data platforms
• Implement strategies directed at acquiring data and promoting the development of new insights across the business
• Own and extend the business's data pipeline by collecting, storing, processing, and sustaining large data sets
• Monitor the existing metrics, analyze data, and lead partnerships with other teams to identify and implement data management process improvements
• Builds a metadata system where all available data is maintained and cataloged
• Design, architect, implement and support critical datasets that avail structured and timely access to actionable business insights
• Oversee activities of junior data engineers, ensuring proper execution of their duties and alignment with business vision and objectives
• Collaborate with other teams, gathering technical requirements for exceptional data management across the various business lines and the business at large
• Develop and manage scalable data processing platforms that support exploratory data analysis and real-time analytics
• Oversee, design, and develop algorithms for real-time data processing within the business and create frameworks that enable quick and efficient data acquisition
• Contribute to the continual improvement of the business's data platforms through observations and well-researched knowledge
• Keep track of industry best practices and trends and take advantage of process and system improvement opportunities through acquired knowledge
• Draft reports and prepare presentations for senior data science and AI/ML leadership. These reports and presentations must be clear, concise, unambiguous, engaging, and convincing, which will demand exceptional communication skills

• Hold a bachelor’s degree in Computer Science, Applied Mathematics, Engineering, or technology-related field
• Possess five (5) years of working experience in the data engineering field, preferably as a Data Engineer in a fast-paced environment and complex business setting
• Deep passion for data and how it can be used to drive new insights. Must possess an ability to design and operationalize high-performance data pipelines that conduct complex data wrangling of large data volumes
• Must be an expert in SQL, NoSQL, Python, R and have a keen understanding of data modeling, data mining, and data warehousing concepts
• United States Citizenship

• Master's degree or Ph.D. in Computer Science, Statistics, Mathematics, or Information Systems
• Demonstrated experience in building and maintaining reliable and scalable data platforms as well as working knowledge of varied forms of data infrastructure inclusive of relational databases such as Postgres, non-relational databases such as MongoDB, and time-series databases such as InfluxDB
• Experience with machine learning, data warehousing, data lakes, and big data infrastructure inclusive of Hadoop, AWS, and container technology such as Docker
• Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to engineering teams and business audiences
• Proven ability to convey rigorous technical concepts and considerations to non-experts
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

• Ability to work as part of a team while maintaining independent thinking
• Self-driven and self-starter, in addition to excellent communication skills
• Great at thinking outside the box and have an aptitude for innovation and problem solving

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