Staff Data Architect
Posted Updated
Summary
Define AI-driven data architecture for a sports-betting platform, designing agentic pipelines, ML-ready data flows, and standards to scale AI across systems.
You will define the architectural direction for applying AI and machine learning across data platforms. You will design AI-assisted data pipeline systems, build reusable AI-native tools, establish standards for ML-ready data flows, evaluate emerging technologies, oversee system performance and reliability, and align stakeholders across the organization.
Responsibilities
- Own the architectural vision for applying AI across the data platform
- Architect an agentic AI-assisted data pipeline factory
- Design and evolve AI-native tools and services
- Define architecture for advanced ML and deep learning workloads
- Establish reference architectures, contracts, and standards
- Prevent fragmentation and duplication across AI and ML efforts
- Partner with data, ML, and engineering teams
- Evaluate emerging AI, ML, and data technologies
- Oversee performance, cost, and reliability of AI and ML data systems
- Communicate the value and direction of the work to stakeholders
Requirements
- 7+ years of experience in data architecture, data platforms, and Big Data
- ML engineering
- Data warehousing
- Streaming
- Big Data
- AI/ML systems
- Databricks
- dbt
- Spark
- Data modeling
- Advanced ML
- Deep learning
- Vector search
- Semantic search
- AI tooling
- Agents
- Version control
- Automated testing
- Reproducibility
- Batch processing
- Data security
- Compliance
- Bachelor's degree in Computer Science or a related field
Benefits
- Health insurance
- Fertility programs
- Family planning
- Mental health support
- Fitness benefits
- Paid time off
- Sick leave
- Annual bonus
- Long-term incentives
- 401(k) matching up to 5%
- Commuter benefits
- Pet insurance
- Life insurance
- Disability insurance
- Paid company holidays