AI Data Engineer

•    The ideal candidate will have experience working with medium to complex data structures in a corporate environment. They should be proficient in working hands-on with data in Snowflake, transforming data with DBT, and visualizing it efficiently in Power BI, including implementing logic in DAX. Additionally, the candidate should possess strong problem-solving skills, attention to detail, and the ability to communicate complex technical concepts to both technical and non-technical stakeholders in English.

Responsibilities:
•    Collaborate with data modelers to prepare and optimize datasets for AI model training and inference.
•    Design and implement data pipelines that support AI/ML workflows, including feature engineering and model monitoring.
•    Integrate AI-powered analytics and predictive models into business intelligence tools like Power BI.
•    Evaluate and implement AI services (e.g., Azure Cognitive Services, OpenAI, or custom ML models) to enhance data products and user experiences.

Qualifications:
•    SQL, DBT, ADF, DAX, Power BI, Snowflake
•    AI/ML Integration: Experience integrating AI/ML models into data pipelines and analytics platforms.
•    Data Modeling: Hands-on experience in designing and implementing complex data models, with a strong understanding of normalization, denormalization, and schema designs such as star schema and snowflake schema.
•    Ingestion Processes: Hands-on experience in developing and optimizing EL (Extract and Load) processes using ADF (Azure Data Factory).
•    Data Transformation Processes: Hands-on experience in developing and optimizing DBT (Data Build Tool) models, including data testing.
•    Data Warehousing: Understanding of data warehousing concepts and best practices, particularly with the Snowflake platform, including optimization strategies, query tuning, and clustering.
•    Cloud Platforms: Experience with Azure, particularly in relation to data storage, integration, processing, and AI services.
•    Programming Languages: Proficiency in SQL and DAX; familiarity with Python or R for AI/ML tasks is a plus.
•    Visualization Expertise: Experience creating interactive and performant visualizations using Power BI, including designing and maintaining semantic models.
•    AI Training & Development: Experience working with the data, systems, and architecture to train and develop new AI-powered analytics and functionality.

Relevant Certifications:
•    PL-300: Power BI Data Analyst Associate
•    DP-203: Azure Data Engineer Associate
•    SnowPro® Core Certification
•    SnowPro® Advanced: Data Analyst
•    SnowPro® Advanced: Data Engineer (DEA-C02)
•    AI-102: Designing and Implementing an Azure AI Solution (Recommended)
•    MS Certified: Azure AI Engineer Associate (Optional but valuable)

Top 3 skill sets/technologies required:
•    AI/ML
•    Data Modeling
•    Power BI