Staff Software Engineer

🕒 February 6

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Fanatics, Inc.

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

🎮 Gaming

🛒 Retail

🛍️ eCommerce

Gaming • Retail • eCommerce

Fanatics is building a leading global digital sports platform that aims to enhance the fan experience for over 100 million sports enthusiasts worldwide. The company operates across several divisions including Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming. They offer fans the opportunity to buy licensed fan gear, jerseys, lifestyle products, and headwear, collect physical and digital trading cards, sports memorabilia, and other digital assets, as well as engage in sports betting. Fanatics partners with over 900 sports properties globally, including major leagues, teams, and athletes, and operates more than 2,000 retail locations. The company is committed to corporate responsibility with a focus on philanthropy, diversity and inclusion, brand protection, and sustainability.

📋 Description

• Lead discovery, design, and architecture for complex, multi-domain projects that shape our platform strategy • Architect highly scalable, fault-tolerant, mission-critical systems on cloud platforms (AWS, Azure, or GCP) handling millions of transactions • Drive full project lifecycles independently, from technical vision through production delivery and operational excellence • Design and implement next-generation microservices, APIs, and platform infrastructure ensuring scalability, reliability, and security • Provide strategic technical direction and serve as trusted advisor to engineering teams and senior stakeholders • Anticipate technical issues, design for failure recovery, and triage complex system-wide performance problems • Write complete, actionable stories and break down complex initiatives into executable work streams • Communicate design trade-offs clearly to both technical teams and senior leadership, influencing architectural decisions • Establish best practices, design patterns, and architectural standards across the organization • Champion engineering culture, continuous improvement, and technical excellence • Mentor and develop engineers across multiple teams, raising the technical bar organization-wide • Collaborate with cross-functional teams including Product, UX/UI, Analytics, and Business stakeholders to define platform requirements • Drive initiatives to enhance platform scalability, stability, security, compliance, and governance • Choose optimal technology stacks considering performance, scalability, cost, maintainability, and integration • Develop observability, monitoring, and operational strategies for highly available systems • Lead adoption of AI/ML capabilities to enhance system reliability, developer productivity, and customer experience • Define and drive migration strategies, version management, and backward compatibility approaches

🎯 Requirements

• Bachelor's degree or equivalent practical experience; Master’s degree preferred. • 10 years of experience in software development, and with data structures/algorithms. • 5+ years of experience in Cloud Architecture and Big Data technologies such as Apache Spark, Flink, Amazon EMR, Kafka, Hive, Redshift, Snowflake. • Expertise in SQL technologies and RDBMS (PostgreSQL, AWS RDS, MySQL). • Must have experience in building Data Platforms – designing and building data models, integrating data from many sources, building ETL and data-flow pipelines, and supporting all parts of the data platform. • Strong problem-solving abilities and a passion for tackling complex technical challenges. • Must have experience in developing application with high performance and low latency • Experience in Web Services, API integration, Data exchanges with third parties is preferred. • Data Analysis skill – can make arguments with data and proper visualization. • Energetic, enthusiastic, detail-oriented, and passionate about producing high-quality analytics deliverables. • Proven expertise in hands-on engineering on cloud platforms (AWS, Azure, or GCP), including but not limited to: data ingestion, transformation, processing, storage, and serving. Demonstrated experience with cloud-native services for data engineering, such as data lakes, data warehouses, data pipelines, and serverless computing.

🏖️ Benefits

• Flexible working hours • Professional development opportunities