Software Engineer II - Data

Fanatics

New York, NY

Full Time

Mid Level

4 days ago

Job Description

About the Role

As Software Engineer II at Fanatics Betting &amp; Gaming (FBG) with a focus on Data Pipelines and service infrastructure, you will be a critical part of our efforts to build and enhance data infrastructure supporting advanced AI and machine learning initiatives. Your role will focus on designing, developing, and maintaining robust data pipelines and integrations that facilitate AI-driven insights, predictive analytics, and real-time operational enhancements. Working closely with data scientists, AI engineers, and cross-functional stakeholders, you will ensure the reliable and efficient delivery of data solutions that empower innovative AI applications and strategic decision-making.

Key Responsibilities

Design, build, and optimize scalable data pipelines tailored for AI and machine learning workflows, including ingestion, processing, and analytics.
Collaborate with data scientists and AI engineers to understand data requirements and support AI model training, validation, and deployment.
Integrate data sources from diverse internal and external systems (Salesforce, Slack, Tableau, AWS services) into cohesive analytics platforms.
Maintain high-quality data standards through rigorous data modeling, data quality checks, governance practices, security measures, and compliance protocols.
Develop and enhance monitoring, testing, debugging, and observability tools to support AI model performance and data pipeline reliability.
Participate in code reviews, architectural decisions, and ensure adherence to best practices for scalability, reliability, and maintainability within AI environments.
Create dashboards and observability solutions (metrics, alerts, logs) to proactively monitor system health, data integrity, and performance.

Requirements

3 - 7 years of professional experience in data engineering, with specific experience supporting data-intensive AI and ML environments.
Hands-on experience with AWS cloud services, particularly AWS Bedrock, S3, Redshift, and MongoDB.
Proficiency in Python, SQL, and familiarity with data orchestration tools like Airflow, Prefect, or similar.
Experience in designing and implementing data models for both relational and non-relational databases.
Solid understanding of REST APIs, microservices architectures, and system integration practices.
Familiarity with observability practices (logs, metrics, traces) and experience with CI/CD pipelines.
Strong analytical and problem-solving skills, comfortable navigating ambiguity and collaborating across teams.

Nice to Have

Direct exposure to AWS Bedrock or equivalent AI and ML managed services.
Experience with real-time streaming data technologies (Kafka, Kinesis).
Background or strong interest in AI-driven analytics, predictive troubleshooting, conversational intelligence, and operational analytics.
Familiarity with applications of data engineering in gaming, sports betting, or other consumer-focused industries.
Enthusiasm for continuous learning about AI advancements, data engineering best practices, and cloud technologies.
Experience working with Salesforce or other related products or a firm understanding of customer success workflows.
Experience building front-end applications using modern frameworks (React, Angular, Vue) and familiarity with UI/UX design principles.