AI Data Engineer

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. AI Engineering Responsibilities: o Collaborate with data modelers to prepare and optimize datasets for AI model training and inference. o Design and implement data pipelines that support AI/ML workflows, including feature engineering and model monitoring. o Integrate AI-powered analytics and predictive models into business intelligence tools like Power BI. o Evaluate and implement AI services (e.g., Azure Cognitive Services, OpenAI, or custom ML models) to enhance data products and user experiences. Required Skills and Experience o SQL, DBT, ADF, DAX, Power BI, Snowflake o AI/ML Integration: Experience integrating AI/ML models into data pipelines and analytics platforms. o 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. o Ingestion Processes: Hands-on experience in developing and optimizing EL (Extract and Load) processes using ADF (Azure Data Factory). o Data Transformation Processes: Hands-on experience in developing and optimizing DBT (Data Build Tool) models, including data testing. o Data Warehousing: Understanding of data warehousing concepts and best practices, particularly with the Snowflake platform, including optimization strategies, query tuning, and clustering. o Cloud Platforms: Experience with Azure, particularly in relation to data storage, integration, processing, and AI services. o Programming Languages: Proficiency in SQL and DAX; familiarity with Python or R for AI/ML tasks is a plus. o Visualization Expertise: Experience creating interactive and performant visualizations using Power BI, including designing and maintaining semantic models. o AI Training & Development: Experience working with the data, systems, and architecture to train and develop new AI-powered analytics and functionality. Relevant Certifications o PL-300: Power BI Data Analyst Associate o DP-203: Azure Data Engineer Associate o SnowPro® Core Certification o SnowPro® Advanced: Data Analyst o SnowPro® Advanced: Data Engineer (DEA-C02) o AI-102: Designing and Implementing an Azure AI Solution (Recommended) o Microsoft Certified: Azure AI Engineer Associate (Optional but valuable) • Top 3 skill sets/technologies required for qualification: o 1): AI/ML o 2): Data Modeling o 3): Power BI Primary skill set (mandatory technical skill sets) : • Strong knowledge in SQL • Develop Data Integration and ETL solutions (preferred Microsoft Platform – SSIS or Azure) • Business Intelligence tools (preferred Microsoft Platform – Power BI, SSRS, SSAS – or Tableau) Must Have skill sets : • Programming language (Python is preferred) • Cloud fundamentals (Azure or AWS) • Data Pipeline and Analytics architectures • Fluent written and spoken English Nice to Have skill sets : • Snowflake • Azure Data Factory • BODS • DevOps fundamental