Cloud Data AI Engineer

What we're looking for

• Lead the design, development, and implementation of highly scalable and secure data warehouse solutions on Snowflake, including schema design, data loading, performance tuning, and optimizing cloud costs.
• Design and build robust, efficient data pipelines (ETL/ELT) using advanced data engineering techniques. This includes hands-on experience in data integration via direct APIs (REST/SOAP) and working with various integration tools (e.g., Talend, stitch, Fivetran, or native cloud services).
• Develop and implement high-impact visual analytics and semantic models in Power BI. Apply advanced features such as DAX, Row-Level Security (RLS), and dashboard deployment pipelines.
• Proficiency in Python/R, familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch), experience with MLOps concepts, and deploying models into a production environment on cloud platforms.
• Develop and deploy AI/ML solutions using Python, Snowpark, or cloud-native ML services (AWS Sagemaker, Azure ML).
• Exposure to LLM/GenAI projects (chatbot implementations, NLP, recommendation systems, anomaly detection) is highly desirable.
• Implement and manage data solutions utilizing core services on at least one major cloud platform (AWS or Azure).
• Demonstrate exceptional communication and articulation skills to engage with clients, gather requirements, and lead project delivery from ground up (inception to final deployment).

Required Qualifications:

• Experience with Tableau or other leading BI tools.
• Working knowledge of Databricks (e.g., Spark, Delta Lake).
• Experience or strong understanding of Data Science methodologies and statistical modeling.
• Relevant industry certifications, including Power BI, Snowflake, Databricks and AWS/Azure Data/AI credentials.

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