Azure Data AI Architect

Reach Beyond!: CHC provides unmatched helicopter services that enable our customers to reach beyond – to work in remote and challenging destinations that limit others – and come home safely. We are dedicated to our purpose of getting our customers where they need to be, when they need to be there, anywhere in the world – safely and reliably. All you have to do is get on board!

At CHC, we pride ourselves on our values and culture:
Accountability: Take pride and ownership of our actions and results.
Collaboration: Working together with transparency and trust to drive continuous improvement.
Care: Creating a safe and sustainable environment for all.
Integrity: Doing what's right and fostering a culture of respect.
Excellence: Prioritizing quality services and setting industry standards.
Role Summary: Key Responsibilities:

• Data Architecture Strategy: Design and implement comprehensive Azure data platform architectures supporting real-time and batch analytics for helicopter operations, maintenance scheduling, and fleet optimization
• AI/ML Solution Development: Architect and deploy machine learning models and AI solutions for predictive maintenance, flight path optimization, resource allocation, and operational efficiency improvements
• Data Platform Migration: Lead the migration of on-premises data warehouses, analytics systems, and reporting platforms to Azure-native services including Synapse Analytics, Data Factory, and Databricks
• Advanced Analytics Implementation: Build modern data lakehouse architectures using Azure Data Lake Storage, Delta Lake, and Fabric to enable self-service analytics and data democratization
• Predictive Maintenance Solutions: Develop AI-powered predictive maintenance systems leveraging IoT data from helicopters to predict component failures and optimize maintenance schedules
• Real-time Analytics: Design streaming analytics solutions using Azure Stream Analytics and Event Hubs to process telemetry data, flight operations, and maintenance events in real-time
• Data Governance & Quality: Establish data governance frameworks, data quality monitoring, and metadata management systems to ensure data integrity across the organization
• MLOps Implementation: Build robust machine learning operations pipelines for model deployment, monitoring, and lifecycle management using Azure ML Studio and MLflow
• Collaboration & Innovation: Partner with operations teams, maintenance engineers, and business stakeholders to identify AI/ML opportunities that drive business value
• Enterprise Integration: Design data integration patterns that connect legacy systems, operational technology, and cloud-native applications
• Performance Optimization: Implement data optimization strategies including partitioning, indexing, and caching to ensure high-performance analytics at scale
• Knowledge Transfer: Mentor data engineers and analysts, establishing best practices for AI/ML development and data platform utilization

Qualifications, Skills & Attributes:

Required Experience

• 7+ years of data architecture experience with 4+ years focused on Azure data and AI platforms
  
  • Proven experience leading enterprise data platform migrations from on-premises to Azure cloud environments
  • Strong background in machine learning, artificial intelligence, and advanced analytics solution design
  • Experience working with Enterprise Data Services teams in large-scale organizations
  • Track record of delivering business value through data-driven solutions and AI implementations

Technical Expertise

• Azure Data Services: Expert knowledge of Azure Synapse Analytics, Data Factory, Databricks, Data Lake Storage, Cosmos DB, and Fabric
  
  • AI/ML Platforms: Proficiency with Azure Machine Learning Studio, Cognitive Services, OpenAI Service, and MLOps frameworks
  • Analytics & Visualization: Experience with Power BI, Tableau, and advanced analytics tools for self-service BI
  • Data Processing: Strong skills in Apache Spark, Delta Lake, SQL, Python, R, and big data processing frameworks
  • Real-time Processing: Expertise in Azure Stream Analytics, Event Hubs, IoT Hub, and real-time data ingestion patterns
  • Data Engineering: Knowledge of data pipelines, ETL/ELT processes, and data integration patterns

Specialized Knowledge

• Predictive Maintenance: Experience implementing predictive analytics for mechanical systems, preferably in aviation or manufacturing
  
  • IoT Analytics: Understanding of sensor data processing, time-series analysis, and industrial IoT platforms
  • Computer Vision: Knowledge of Azure Computer Vision and custom vision models for inspection and monitoring applications
  • Natural Language Processing: Familiarity with document processing, text analytics, and conversational AI solutions
  • Time Series Forecasting: Experience with demand forecasting, capacity planning, and operational optimization models

Industry Understanding

• Knowledge of helicopter operations, aircraft maintenance, and aviation safety requirements (preferred)
  
  • Understanding of regulatory compliance in aviation industry and safety-critical data handling
  • Experience with ERP systems, CMMS platforms, and operational technology common in aviation
  • Familiarity with supply chain analytics and parts inventory optimization

Certifications (Preferred)

• Azure Data Engineer Associate (DP-203)
  
  • Azure AI Engineer Associate (AI-102)
  • Azure Solutions Architect Expert (AZ-305)
  • Additional relevant Azure data and AI certifications

Attributes

• Business Acumen: Ability to translate complex technical concepts into business value and ROI
• Innovation Mindset: Passion for exploring cutting-edge AI/ML technologies and their practical applications
• Problem-Solving: Analytical thinking with ability to decompose complex business problems into data science solutions
• Communication Skills: Excellent presentation and documentation abilities to engage both technical and executive audiences
• Collaborative Leadership: Experience building consensus across diverse teams and managing stakeholder expectations
• Continuous Learning: Commitment to staying current with rapidly evolving AI/ML technologies and Azure platform updates
• Quality Excellence: Focus on data accuracy, model reliability, and production-ready solutions for mission-critical operations
• Agile Mindset: Adaptability to work in fast-paced digital transformation environments with changing requirements