Role overview
We are seeking a highly skilled and results-driven Modern Cloud Data and AI Engineer with a strong background in modern cloud data architecture, specifically on Snowflake, and hands-on experience in developing Data solutions in Power BI, implementing AI Solutions.
The ideal candidate combines strong data engineering, integration, and BI expertise with hands-on AI project execution, supporting OSI’s reputation for high-impact consulting in cloud and digital transformation spaces and will be a strong communicator, capable of implementing projects from the ground up.
Responsibilities
- 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).
Basic qualifications
- Minimum of 4 years of professional experience in data engineering, consulting, and solution delivery.
- Bachelor’s degree in computer science, Engineering, or a related technical field. A master’s degree in a relevant field is highly preferred.
- Strong, hands-on experience in end-to-end Snowflake project implementation. Any professional certifications in snowflake preferred.
- Expertise in designing, building, and maintaining ELT/ETL pipelines and data workflows, with a solid understanding of data warehousing best practices.
- Hands-on experience implementing dashboards in Power BI, including DAX and RLS. Professional certifications in Power BI are preferred.
- Proficiency in Python, with demonstrable experience deploying at least one AI/ML project (e.g., Snowpark, Databricks, SageMaker, Azure ML) including feature engineering, model deployment, and MLOps practices.
- Experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch, and hands-on exposure to production deployments.
- Familiarity with projects involving LLM/Generative AI (e.g., chatbots, NLP, recommendation systems, and anomaly detection).
- Hands-on experience working with cloud platforms, specifically AWS or Azure.
- Excellent verbal and written communication, presentation, and client-facing consulting skills, with proven track record of successfully leading projects from inception.
- 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.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Ai Engineer Data Engineer