Data Engineer

🕒 July 29

🏄 California – Remote

🏄 California – Remote

💵 $145k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

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Swish Analytics

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

💼 Consulting

📣 Marketing

🎲 Gambling

💰 $6.9M Series B - Swish Analytics on 2019-05

Consulting • Marketing • Gambling

Swish Analytics is a machine-learning driven sports-odds and predictive-data company that builds a real-time odds origination engine for sportsbooks and fantasy platforms. It provides hyper-accurate player prop pricing, match and team markets, in-play and pre-game projections, and automated bet-lifecycle management to power bookmaking, bet builders, parlays, and micro-markets. Swish positions itself as a B2B provider focused on automation, accuracy, and scalable odds infrastructure for the sports betting industry.

📋 Description

• Support production systems and help triage issues during live sporting events • Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production • Build new sports betting data products and predictions offerings • Integrate large and complex real-time datasets into new consumer and enterprise products • Develop production-level predictive analytics into enterprise-grade APIs • Contribute to the design and implementation of new, fully-automated sports data delivery frameworks

🎯 Requirements

• BS/BA degree in Mathematics, Computer Science, or related STEM field • Minimum of 4+ years of demonstrated experience writing production level code (Python) • Proficiency in Python and SQL (preferably MySQL) • Demonstrated experience with Airflow • Demonstrated experience with Kubernetes • Experience building end-to-end ETL pipelines • Experience utilizing REST APIs • 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 • Professional working experience with MLB or NBA data.