Cloud Platform Architect

Principal Software Engineer

The Platforms organization at Fanatics is at the heart of our company's data-driven decision making, building foundational capabilities that empower our application/data engineers and data scientists to unlock the power of data.

1. Commerce Applications: Architecting and designing D2C and B2B commerce applications with workloads distributed across a multi-cloud topology to engage fans around the world.
2. Storage Infrastructure: Building and managing scalable and reliable data storage solutions.
3. Streaming Data Processing: Handling real-time data pipelines with high throughput and low latency.
4. Data & Workflow Orchestration: Coordinating complex data processing workflows with efficiency and reliability.
5. Messaging Infrastructure: Ensuring secure and efficient communication between applications.
6. Big Data Processing: Analyzing massive datasets with speed and accuracy.
7. Data Warehouse: Providing a centralized and accessible repository for historical data.
8. Real Time OLAP Databases: Enabling fast and interactive data analysis for insights on the fly.
9. AI & ML Platforms: Building and maintaining a robust platform that supports the development and deployment of impactful ML models to power applications in areas such as recommender systems and inventory intelligence.

The Opportunity

We are seeking a passionate and experienced Principal Engineer to play a key role in shaping the future of our application, cloud, and data platforms. As a technical leader in the organization, you will be responsible for driving technical innovation, leading large initiatives, and mentoring junior engineers. You will have the opportunity to contribute to building scalable solutions that will empower our entire company to make data-driven decisions and operate more effectively.

Responsibilities

1. Design and drive the technical roadmap for the evolution of our platforms, ensuring they are scalable, reliable, and meet the evolving needs of the business.
2. Lead large initiatives within the broader tech org, collaborating effectively with cross-functional teams including engineering, data science, and product management.
3. Provide mentorship and guidance to junior engineers, fostering their growth and development within the team.
4. Build data platforms that promote standardization, including data pipeline development, platform tooling, data lake formatting, and data democratization.
5. Build and maintain the AI/ML infrastructure to support AI/ML needs, with a focus on standardized MLOps practices, accelerating the adoption and deployment of impactful AI/ML applications across the company.
6. Champion data and AI governance best practices, establishing and enforcing data processing principles, design patterns, and practices.
7. Build strong cross-functional partnerships with teams across the organization, influencing them to adopt best practices and collaborate effectively.

Qualifications

1. 13+ years of experience leading the development of modern cloud-based applications and their integration into a common data platform (or data mesh) to enable business intelligence and optimization.
2. Deep technical understanding of distributed systems architecture and the integration of operational systems with analytical systems to enable anomaly detection, business process mining, and optimization at scale.
3. Strong expertise in the big data ecosystem, including tools like Apache Kafka, Spark, Iceberg, Airflow, AWS S3, data modeling, data warehouses, OLAP databases, etc.
4. Proven experience in data processing, orchestration, data engineering, data quality management, and data governance.
5. Excellent communication skills, with the ability to collaborate effectively across teams and provide clear and concise technical guidance.
6. Experience with AI/ML platforms and a working knowledge of how data scientists leverage data for AI is a strong plus.