The Role

As a Senior Staff Data Engineer in the Fanatics Ecosystem organization, you will provide technical leadership for the design, evolution, and execution of our core data platforms and data flows. This role operates with a high degree of autonomy, owning architectural direction for foundational data systems that span teams, products, and operating companies.

You will work closely with engineering leadership, platform teams, and product partners to ensure data systems are scalable, reliable, and aligned with long-term organizational goals, collaborating across databases, streaming technologies, CI/CD, cloud platforms, and modern data engineering tools. This role emphasizes building durable, reusable data capabilities—particularly in event-driven and streaming contexts—rather than one-off pipelines or analytics solutions.

This position reports directly to the Director of Engineering and serves as a key technical influencer across the organization.

Responsibilities

• Lead the architecture, discovery, design, and implementation of complex data systems and pipelines across multiple domains.
• Own and evolve shared data platforms, including event- and stream-based systems, as long-lived, reusable capabilities.
• Drive strategic technical decisions around architecture, technology selection, and system design with a focus on reliability, cost, and operational sustainability.
• Define and evolve shared data models, schemas, and contracts that enable consistent use of data across teams while respecting local autonomy.
• Partner with product, platform, and engineering leaders to translate ambiguous business needs into clear technical direction and executable plans.
• Establish standards and patterns for building, enriching, and consuming data streams and derived datasets.
• Produce clear technical proposals and documentation that communicate system design, trade-offs, and long-term implications.
• Represent the team in cross-functional planning, architecture reviews, and strategic initiatives.
• Serve as an escalation point for complex technical challenges and high-impact incidents.
• Mentor engineers at all levels and set expectations for technical excellence, design quality, and documentation.
  

Technical Environment
You’ll work across a mix of technologies and systems, including:

• Event-driven and streaming data systems (e.g., Kafka)
• Workflow orchestration and data pipelines (e.g., Airflow)
• Cloud data platforms and warehouses (e.g., Snowflake)
• AWS-native services
• Long-lived backend services supporting data workflows
• Infrastructure as code (e.g., Terraform)
  

Qualifications

• 12+ years of experience in data engineering or related fields, with demonstrated progression into senior or staff-level technical leadership roles.
• Proven experience architecting and operating large-scale, cloud-native data platforms and pipelines.
• Strong understanding of distributed systems concepts, including state, ordering, failure modes, and consistency.
• Experience with event-driven or streaming architectures and the systems that support them (particularly Kafka, Airflow, Snowflake).
• Hands-on experience building and operating data systems in AWS.
• Track record of influencing technical direction across multiple teams or organizations.
• Ability to operate effectively in ambiguous, fast-paced environments and drive clarity through technical leadership.
• Strong written and verbal communication skills, with experience presenting complex technical topics to diverse audiences.
• Experience with data governance, security, and compliance considerations at scale.
• Experience designing and running long-lived backend services is a plus.
• Experience developing in Go and using infrastructure as code (e.g., Terraform) is a strong plus.
  

The salary range for this position is $185,760 to $268,750, which represents base pay only and does not include short-term or long-term incentive compensation. When determining base pay, as part of a final compensation package, we consider several factors such as location, experience, qualifications, and training.