Job Description

Title: Data Engineer Snowflake, SAP HANA Location: Onsite Toronto, Canada Start Date: Immediate Special Notes: Please note this is onsite position Schedule: Standard Business Hours, Monday to Friday Description Job Summary We are looking for a highly skilled Data Engineer with proven experience in Snowflake, SAP S4 HANA, and enterprise data integration, who can also assist in setting up data pipelines from SAP HANA to C3.ai or similar Enterprise AI platforms. This is a 3 to 6-month onsite contract role in Toronto, where the ideal candidate will work closely with data, AI, and business teams to build robust pipelines enabling AI-driven analytics. Key Responsibilities Design, implement, and manage scalable ETL/ELT pipelines using Snowflake. Extract and transform data from SAP S4 HANA and InfoFlow for downstream analytics and AI consumption. Build and operationalize a data integration pipeline from SAP HANA to C3.ai or similar Enterprise AI platforms, ensuring clean, high-quality, structured datasets for modeling. Support AI and data science teams with real-time and batch data feeds into C3.ai or equivalent platforms. Work with system owners to understand business data, source schemas, and transformation logic. Ensure data lineage, governance, and auditability are maintained across systems. Optimize pipeline performance, monitor failures, and ensure high availability of the data pipeline architecture. Required Skills & Qualifications 4+ years of experience in data engineering with strong knowledge of data integration and warehouse concepts. Proficiency in Snowflake, SQL, and scripting (e.g., Python, Shell). Hands-on experience with SAP S4 HANA integration (including CDS Views, OData/ODBC/JDBC extractions, or SLT). Experience with InfoFlow or similar data pipeline orchestration tools. Proven experience integrating enterprise data with C3.ai or similar platforms (e.g., Palantir, Azure ML, Google Vertex AI, SAS AI, etc.). Deep understanding of enterprise data architecture, ETL best practices, and data modeling. Familiarity with security and compliance standards in enterprise environments (e.g., PIPEDA, GDPR). Preferred Qualifications Experience with cloud platforms (AWS, Azure, or GCP). Familiarity with C3.ai platform architecture, including data ingestion, modeling, and pipeline APIs. Experience with data governance tools and metadata management systems. Exposure to AI/ML pipelines, MLOps, or model deployment workflows.

Job Tags

Contract work, Immediate start, Monday to Friday,

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