Data Engineer

Summary

Join Swish Analytics, a sports analytics startup, as a Data Engineer supporting the Trading Analytics team. You will ensure accurate client data ingestion and reporting to key stakeholders, collaborating with the Trading and Software Engineering teams. This remote position requires expertise in data engineering, reporting, and data visualization. You will maintain data integrity, identify and resolve data quality issues, and integrate large datasets into new products. The role involves developing predictive analytics and automated data delivery frameworks. This is a fast-paced environment requiring a passion for accurate, real-time data.

Requirements

• BS degree or higher in Computer Science, Data Science, Data Analytics or similar major
• Minimum of 1 year of experience writing production level code
• Proficiency in Python (pandas, NumPy)
• Proficiency in SQL (preferably MySQL)
• Experience utilizing REST APIs
• Experience in SQL database management, schema design, index structuring
• Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS)
• Experience with web scraping and cleaning unstructured data
• Knowledge of data science and machine learning concepts

Responsibilities

• Advance data engineering aspects of Trading Analytics, enabling faster and better trading decisions and reducing the reliance on manual reporting
• Lead Trading team and customer based reporting, as well as on-demand data needs for Swish
• In conjunction with Trading Analytics Manager, develop impactful and accurate reports, dashboards, and other data visualizations
• Maintain data integrity and ongoing quality of delivered reports
• Identify data quality issues and work with Data Science, Data Engineering, and Software Engineering teams to resolve challenges
• Integrate large, complex real-time datasets into new consumer and enterprise products
• Develop production-level predictive analytics into enterprise-grade APIs
• Contribute to the implementation of fully-automated sports data delivery frameworks