Join Riverside Natural Foods Ltd., a $300 million+ Canadian-based, family-owned, and globally operating business. We are on an ambitious mission to double our business by 2027 and seek talented individuals to help reach current heights.

As Riverside Natural Foods continues its business transformation, we are investing in data and analytics capabilities to support long-term, values-based growth. A key pillar is evolving a trusted data ecosystem as a foundation for our BI and AI strategy.

The Enterprise

Data & Generative AI Engineer builds and operates the data foundation powering analytics, machine learning, and Generative AI across the organization. This role covers cloud lakehouse platforms (Databricks or Snowflake), syndicated data (e.g., POS, Nielsen), IoT/PLC data from production lines, unstructured data sources, and SAP Datasphere. The engineer ensures that all enterprise data domains are integrated into a governed, scalable, AI-ready Data Fabric that supports advanced analytics and GenAI applications.

This individual should be a self-starter with strong communication skills, curiosity, and a deep understanding of SAP-centric enterprise data architecture with other modern lakehouse data ecosystems. Support the execution of Riverside’s BI and AI Strategy in alignment with enterprise priorities.

Design and implement scalable ingestion pipelines across different application platforms, including POS feeds, Nielsen syndicated data, IoT/PLC data, and unstructured sources such as documents, logs, and images.

Ensure reliable delivery of current reports consumed by the business and support their transition to better-designed technology.

Optimize pipelines for performance, cost, and reliability across the Data Fabric. Build ELT/ETL workflows that support analytics, ML, and GenAI use cases across structured, semi-structured, and unstructured data based on business priorities.

Develop real-time or near real-time data flows for AI-driven applications using event-driven architectures.

Enterprise Data Architecture

Model and harmonize SAP S/4HANA data structures while integrating them with external commercial, operational,



and sensor data in collaboration with the SAP Analytics Lead.

Integrate SAP and non-SAP data into Databricks or Snowflake to support advanced analytics, ML, and GenAI workloads.

Contribute to the design of a unified Data Fabric that supports cross-domain analytics and AI. Data Governance, Quality & Observability Implement data quality rules, lineage tracking, and metadata management across SAP, cloud, IoT, and syndicated data sources.

Ensure compliance with security, privacy, and regulatory requirements.

Monitor data drift, embedding drift, and AI-specific data quality indicators.

Platform

Engineering & Automation Use infrastructure-as-code and CI/CD to deploy and manage data pipelines and lakehouse components.

Automate documentation, testing, and pipeline optimization using GenAI-assisted tools.

Contribute to the design of enterprise data products that are versioned, governed, and AI-ready. AI/ML & Generative AI Enablement Prepare curated datasets for ML model training, LLM fine-tuning, and enterprise GenAI applications.

Build pipelines for document processing, chunking, and embedding generation to support Retrieval-Augmented Generation (RAG).

Implement and maintain vector databases or embedding stores.

Support synthetic data generation and data augmentation workflows.

Collaborate with ML engineers to operationalize model training, evaluation, and monitoring. Partner with BT&T; and business stakeholders to translate priorities into scalable data solutions that support analytics and GenAI.

Provide technical guidance on data architecture decisions involving SAP Datasphere, Databricks, Snowflake, and IoT/OT data platforms.

Be a Riverside Brand Ambassador, staying close to consumers and protecting product quality, availability, and experience.



Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.

5+ years of CPG experience in BI, Data Engineering, or Analytics roles preferred.

Prior work integrating SAP with cloud lakehouse platforms.

Experience with IoT/OT data ingestion and industrial data protocols and hybrid SAP + cloud analytics architectures.

Technical Skills

Strong SQL and Python for data engineering.

Experience with SAP S/4HANA data structures and integration patterns (ODP, CDS views, SAP BTP services).

Hands-on experience with SAP Datasphere modeling and data integration.

Proficiency with Databricks (Spark, Delta Lake) or Snowflake (Snowpark, Streams/Tasks).

Familiarity with cloud platforms (Azure, AWS, or GCP).

Experience with orchestration tools such as Airflow, dbt, or SAP Data Intelligence.

Experience building pipelines for unstructured data (documents, images, logs).

Familiarity with vector databases (FAISS, Pinecone, Weaviate, or cloud-native equivalents).

Exposure to ML lifecycle tooling (MLflow, SageMaker, Vertex AI, or Databricks ML).

Ability to support model monitoring and AI observability preferred. You are a strong communicator and enjoy working with both business and technical teams.

You are passionate about data and helping others make better decisions.

Try new approaches, adjust quickly, and pursue win-win outcomes without compromising quality or trust.

Salary Range: $120,000 CAD - $145,000 CAD exact compensation will be based on experience, skill set, education, and training, as well as internal equity. Help shape the organization and its processes, rolling up your sleeves when needed.

Personal development: We support you to chart your own path with training and tools to grow.

Represent the brand and protect product quality and experience. Courageous determination and resourcefulness in a fast-growing business.

Continuous improvement: Employee-Led Resource Groups (ERGs) supporting mental health, sustainability, diversity, and LGBTQ+ rights.

Riverside Natural Foods Ltd. is committed to an inclusive environment.

📌 Data Platform Engineer, Senior (Toronto)
🏢 Riverside Natural Foods Ltd. (Home of MadeGood)
📍 Toronto