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# Data Engineer

- **Company:** REMOTE HAND
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $145,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Continuous Integration, Web Scraping, Extract Transform Load (ETL), Data Systems, Python (Programming Language), MySQL, Shell Script, SQL Databases, Systems Integration, Unstructured Data, Software Troubleshooting, Git, Build Management, Kubernetes, Information Technology, Low Latency, Real Time Data, Data Delivery, Restful APIs
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pecimu7fh1

## About the Role

* Bachelor's degree in Mathematics, Computer Science, or a related STEM field

 * Minimum 4 years of experience writing production-level Python code

 * Strong proficiency in Python and SQL, preferably MySQL

 * Experience with Airflow and Kubernetes

 * Proven experience building end-to-end ETL pipelines

 * Experience developing and integrating REST APIs

 * Familiarity with Git, CI/CD, shell scripting, and AWS cloud infrastructure

 * Experience with web scraping and cleaning unstructured data

 * Knowledge of data science and machine learning concepts

 * Professional experience working with MLB or NBA data

 * Strong troubleshooting and problem-solving skills

 * Ability to work effectively in a remote, collaborative environment

## Description

The Data Engineer supports the infrastructure and delivery of core consumer and enterprise data products, with a focus on expanding coverage of non-U.S. sports. This remote role involves building and maintaining real-time analytics systems, developing data products, and strengthening data delivery frameworks that support accurate predictions.

The position also contributes to production systems supporting live sporting events, requiring strong technical problem-solving and the ability to work with high-volume, real-time data.

Responsibilities

 * Support production systems and resolve issues during live sporting events

 * Design and build low-latency, real-time analytics systems, including data collection, feature development, and endpoint production

 * Develop new sports betting data products and predictive offerings

 * Integrate complex real-time datasets into consumer and enterprise products

 * Create production-grade predictive analytics APIs

 * Design and implement automated sports data delivery frameworks

 * Build and maintain end-to-end ETL pipelines

 * Improve data quality, reliability, and availability across analytics systems

 * Collaborate with data science and engineering teams to deliver scalable data solutions


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