Job Title:
Cloud Data \& AI Engineer
Employment:
Full-time
At OSI Digital Inc, we accelerate our client’s digital transformation journey by delivering modern data solutions, enabling them to unlock the full potential of their data with scalable cloud platforms, intelligent analytics, and AI-driven solutions. With deep expertise across data engineering, cloud platforms, advanced analytics, and AI/ML, our teams bring both technical mastery and business acumen to every engagement. We don’t just implement tools—we build scalable, future-ready solutions that drive measurable outcomes for our clients.
Role Summary:
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.
Key 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)
Required 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
Preferred (Added Advantage) 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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