- Design and optimize data models, feature stores, and storage patterns to ensure performance, reliability, and governance across AI workloads
- Build and maintain scalable batch and streaming data pipelines that ingest, transform, and curate high-quality datasets for AI and agentic workflows
- Implement DataOps and MLOps automation, including CI/CD pipelines, data validation, ML model deployment, monitoring, and drift detection
- Write production-quality code, conduct thorough code reviews, troubleshoot performance issues, and continuously enhance system reliability, scalability, and observability

Requirements

- Bachelor’s degree in computer science, Software Engineering, or related field, plus experience in data, software, ML, or AI engineering
- Strong SQL and database fundamentals (both relational and NoSQL)
- Proficiency in production-grade coding with strong software engineering fundamentals including version control, testing, and code review practices
- Deep expertise in data modeling, distributed systems, storage optimization, and performance tuning for large-scale AI and analytics workloads
- Solid understanding of the ML data lifecycle, including feature engineering, model integration, deployment support, and monitoring




- Excellent communication and collaboration skills with the ability to translate complex business requirements into well-architected technical solutions; proven ability to work effectively across product, platform, and cross-functional engineering teams

Core Competencies

Demonstrates expertise in designing and optimizing data models and pipelines for AI workloads, with a robust foundation in DataOps and MLOps practices. Proficient in production-grade coding and collaboration across cross-functional teams to deliver high-quality technical solutions.

Highest-signal resume keywords

- Data Modeling
- MLOps Automation
- SQL Proficiency
- Production-Grade Coding
- Data Pipeline Development

Hard Skills

- Data Modeling
- SQL
- NoSQL
- DataOps
- MLOps
- Feature Engineering
- Performance Tuning
- Code Review
- Version Control
- Testing

Soft Skills

- Communication
- Collaboration

Industry Keywords

- AI Workloads
- Data Validation
- ML Model Deployment
- Monitoring
- Drift Detection
- Distributed Systems
- Storage Optimization
- Analytics Workloads

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📌 Data/AI Engineer (Vancouver)
🏢 Jobtailor
📍 Vancouver