Description

You will own the data infrastructure powering AI/ML workflows, from ingestion to visualization. You design and implement pipelines that support feature engineering, model training, and monitoring. You integrate AI services into business intelligence tools and optimize datasets for inference.

Responsibilities

• Collaborate with data modelers to prepare and optimize datasets for AI model training and inference.
• Design and implement data pipelines supporting AI/ML workflows, including feature engineering and model monitoring.
• Integrate AI-powered analytics and predictive models into Power BI using DAX logic.
• Evaluate and implement Azure Cognitive Services, OpenAI, or custom ML models to enhance data products.
• Optimize Snowflake data warehousing through query tuning, clustering, and schema design.

Required Skills

• 12+ years of experience in data engineering or analytics roles.
• Proficiency in SQL, DBT (Data Build Tool), and Azure Data Factory (ADF).
• Hands-on experience with Snowflake, including optimization strategies and data warehousing concepts.
• Strong skills in Power BI and DAX for efficient data visualization and logic implementation.
• Experience integrating AI/ML models into data pipelines and analytics platforms.
• Hands-on experience in designing complex data models (star schema, snowflake schema).
• Proficiency in Python or R for AI/ML tasks.
• Experience with Azure cloud platforms for data storage, integration, and AI services.
• Strong problem-solving skills and ability to communicate technical concepts to diverse stakeholders.

Preferred Skills

• Relevant certifications: PL-300, DP-203, SnowPro Core/Advanced, or AI-102.
• Experience training and developing new AI-powered analytics functionality.

Key Skills

Education

Any Graduate