Senior Data Engineer, Gametime

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent experience
• 5+ years of experience in data engineering, software engineering, or platform development
• Strong fluency in SQL and Python for both pipeline development and data analysis
• Deep experience with modern data warehouses (e.g., Snowflake) and cloud infrastructure (AWS preferred)
• Expertise with workflow orchestration tools like Airflow and data transformation tools like dbt
• Solid understanding of data modeling, software design principles, and engineering best practices

Desirable

• Gametime is seeking a Senior Data Engineer to help shape the future of our data platform
• In this high-impact role, you’ll lead the design, implementation, and evolution of core data systems that power decision-making across analytics, product, marketing, and operations
• You’ll own critical infrastructure across both batch and streaming pipelines, contribute to architectural strategy, and partner with stakeholders across the business to build scalable, reliable data solutions
• As a senior member of the team, you’ll provide technical leadership, drive best practices, and mentor others as we continue to scale
• We’re operating on a modern, event-driven stack, and you’ll play a key role in growing and hardening our capabilities in areas like observability, real-time processing, and platform reliability
• Real-Time Streaming: Design and implement streaming data solutions using Confluent Kafka
• Architect and Own Core Data Infrastructure: Design and lead implementation of scalable, resilient batch and streaming pipelines using Airflow, Python, and Kafka
• Lead Platform Evolution: Shape the roadmap and technical direction of the Data Platform, advocating for best practices in architecture, observability, cost efficiency, and quality
• Model & Transform Data: Own development of modular, production-grade dbt models that surface business logic for downstream analytics and data science
• Infrastructure as Code: Manage deployment of cloud infrastructure via Terraform across AWS environments
• Drive Quality and Monitoring: Establish and improve systems for data validation, pipeline reliability, and automated alerting
• Mentor & Collaborate: Provide technical leadership through code reviews, architecture discussions, and mentorship across the data and engineering orgs
• Cross-Team Partnerships: Work closely with stakeholders in Product, Analytics, and Engineering to scope and deliver impactful data initiatives
• What success looks like:
• Lead and deliver major platform initiatives that improve scalability, reliability, or usability of the data stack
• Reduce platform maintenance by automating operational workflows and improving observability
• Drive architectural improvements that reduce query cost, improve performance, or unblock new use cases
• Influence engineering culture by mentoring teammates, improving documentation, and driving technical standards