Software Engineer III - Data

About the Role

Key Responsibilities

• Lead the design, development, and optimization of scalable and reliable data pipelines tailored for complex AI and machine learning workflows.
• Provide technical guidance and mentorship to engineering teams, ensuring best practices in data management, architecture, and performance.
• Work collaboratively with data scientists and AI engineers to understand complex data requirements and facilitate seamless AI model integration, training, and deployment.
• Drive the integration and harmonization of diverse data sources from internal and external systems (Salesforce, Slack, Tableau, AWS services) into unified analytics platforms.
• Maintain exemplary data standards, emphasizing rigorous data modeling, quality assurance, governance, compliance, and security protocols.
• Develop and enhance advanced monitoring, debugging, and observability systems to ensure robust pipeline performance, system health, and data integrity.
• Lead architecture discussions and code reviews to maintain high standards of scalability, maintainability, and reliability across AI-focused infrastructures.
• Create and oversee the implementation of dashboards and comprehensive observability tools (logs, metrics, alerts) that proactively monitor and enhance operational performance.
• Prototype, develop, and refine advanced, user-friendly UI screens and dashboards, enabling customer success teams to leverage AI-driven insights effectively.

Requirements

• 6 - 10 years of professional experience in data engineering, specifically managing data-intensive infrastructures supporting AI and ML systems.
• Proven expertise with AWS cloud technologies, notably AWS Bedrock, Redshift, MongoDB, and S3.
• Advanced proficiency in Python, SQL, and data orchestration frameworks such as Airflow, Prefect, or similar technologies.
• Extensive experience designing, implementing, and optimizing data models for both relational and non-relational database systems.
• Deep understanding of REST APIs, microservices architectures, and system integration methodologies.
• Extensive familiarity with observability practices (logs, metrics, traces) and robust CI/CD pipeline management.
• Exceptional analytical and problem-solving abilities, adept at navigating ambiguity and driving clear technical direction within diverse teams.

Nice to Have

• Direct experience with AWS Bedrock or equivalent managed AI and ML services.
• Significant experience implementing and optimizing real-time streaming technologies (Kafka, Kinesis).
• Background in advanced AI-driven analytics, predictive troubleshooting, conversational intelligence, and operational analytics.
• Familiarity with data engineering applications within gaming, sports betting, or other dynamic consumer-facing industries.
• Enthusiasm for continuous learning and staying ahead of emerging trends in AI, data engineering, and cloud technology best practices.
• Experience with Salesforce integration and a deep understanding of customer success workflows.
• Experience developing front-end applications using modern frameworks (React, Angular, Vue) and strong familiarity with UI/UX design principles.