Data Modeling Engineer

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.

Swish Analytics is looking for a Data Modeling Engineer to join our ever-growing team! Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products.  

This position is 100% remote.

Duties

• Design and build reusable components, frameworks, and libraries at scale to support the Data and Data Science teams
• Researching and making recommendations on Python tools & libraries to improve reliability, performance, scalability, and maintainability of core products.
• Identify and solve issues concerning data management to improve data quality
• Clean, prepare and optimize data for ingestion and consumption
• Analyze and profile data for the purpose of designing scalable solutions
• Collaboratively review design, code, test plans and dataset implementation performed by other data scientists and engineers in support of maintaining programming standards
• Implement automated workflows and routines using workflow scheduling tools
• Build continuous integration, test-driven development, and production deployment frameworks
• Collaborate on the implementation of new data management projects and on the restructuring of the current data architecture
• Mentor others on the team while owning independent deliverables.

Requirements

• Bachelor/Master degree in Computer Science or related technical subject area or equivalent combination of education and experience
• 7+ years of relevant experience in large-scale software development
• 5+ years of data engineering experience.
• Strong understanding of algorithms, data structures, data architecture, and technical designs.
• Strong experience with relational SQL and programming languages such as Python
• Experience working with Big Data streaming services such as Kafka, etc.
• Experience provisioning RESTful APIs to enable real-time data consumption
• Experience with workflow scheduling tools like Airflow.
• Proven ability to quickly pick up new languages, technologies, and frameworks.