Data Engineer - Expert Level

Primary skill set (mandatory technical skill sets) :

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 :

• 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.

Required Skills and Experience

Relevant Certifications

Top 3 skill sets / technologies required for qualification :

The biggest factor in our selection process is that the candidates demonstrate experience in their resumes engineering and implementing AI-ready data systems in Snowflake, transforming data with DBT, and visualizing it efficiently in Power BI, including implementing logic in DAX.