Enterprise Data & Generative AI Engineer

Position Summary:

Riverside Natural Foods is investing in modern data and analytics capabilities to support business growth and innovation. As part of this transformation, Databricks is becoming the central platform for all non-SAP data, enabling advanced analytics, reporting, and emerging AI use cases.

The Data Platform Engineer (Databricks) will play a key hands-on role in designing, building, and operating this platform. This role is responsible for delivering end-to-end data solutions—from ingestion and transformation to modelling and consumption—while shaping best practices for scalable, reliable, and high-performing data pipelines.

This is a highly hands-on role ideal for someone who enjoys building, solving complex data challenges, and owning technical delivery within a modern cloud data platform.

Primary Responsibilities:

1. Databricks Platform Ownership

Design, build, and maintain the Databricks platform as the central hub for non-SAP data

Define and implement best practices for data architecture, pipeline development, and platform usage

Ensure platform scalability, performance, reliability, and cost efficiency

2. Data Engineering & Pipeline Development

Develop and maintain scalable data pipelines using Databricks

Ingest data from a variety of sources, including APIs and external data providers, streaming platforms (e.g., Kafka), Internal non-SAP systems, etc.

Build ETL/ELT workflows to support analytics and reporting needs

Support both batch and streaming data processing patterns

3. Data Modeling & Architecture

Design and implement data models to support analytics and reporting use cases

Define how data is structured, stored, and accessed within Databricks

Enable integration with SAP Datasphere where required, while maintaining flexibility for independent datasets

4. End-to-End Data Delivery

Deliver complete data solutions from ingestion to consumption

Collaborate with analytics and reporting team members to ensure data usability and performance

Support downstream use cases, including dashboards, reporting, and advanced analytics

5. AI & Advanced Analytics Enablement

Enable AI and advanced analytics capabilities within Databricks

Support data preparation for machine learning and AI-driven use cases

Leverage built-in Databricks features to accelerate innovation

6. Engineering Best Practices & Tooling

Use GitHub for version control and collaborative development

Implement CI/CD practices for data pipelines and platform components

Improve automation, testing, and documentation across the platform

7. Vendor & Partner Collaboration

Work with external partners and contractors when required

Provide guidance to ensure alignment with platform standards and architecture

Maintain quality and consistency across all Databricks deliverables

Qualifications:

Education & Experience

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field
• 5+ years of experience in data engineering, data platform development, or analytics engineering
• Proven experience with IoT/OT data ingestion and industrial data protocols as well as hybrid SAP + cloud analytics architectures.

Technical Skills

• Strong SQL and Python for data engineering.
• Strong hands-on experience with Databricks (must-have)
• Proficiency in SQL and Python
• Experience building scalable data pipelines (ETL/ELT)
• Experience ingesting data from APIs, streaming platforms (e.g., Kafka), or similar technologies
• Experience working with cloud-based data platforms (Azure preferred)
• Experience with version control tools such as GitHub

Nice to Have

• Experience with SAP S/4HANA data structures and integration patterns (ODP, CDS views, SAP BTP services).
• Prior work integrating SAP with cloud lakehouse platforms.
• Hands‑on experience with SAP Datasphere modelling and data integration.
• Familiarity with cloud platforms (Azure, AWS, or GCP).
• Knowledge of streaming technologies (Kafka, Kinesis, or equivalent).
• Understanding of LLMs, embeddings, and RAG architectures.
• Experience building pipelines for unstructured data (documents, images, logs).
• Exposure to ML lifecycle tooling (MLflow, SageMaker, Vertex AI, or Databricks ML).
• Ability to support model monitoring and AI observability.

About You:

• Hands-on and solution-oriented, with a strong sense of ownership
• Comfortable working across the full data lifecycle
• Strong problem-solving and analytical skills
• Effective communicator, able to collaborate with both technical and business teams
• Self-starter who thrives in a fast-paced, evolving environment
• Passionate about building modern data platforms that enable better decision-making
• Naturally take ownership and have a can-do attitude.
• You embody Riverside values of humility, adaptability, respect, and fun—and inspire your team to do the same.
• Be Bold & Courageous: Challenge the status quo, act with intent before conditions are perfect, and learn fast. Try new approaches, adjust quickly, and pursue win-win outcomes without compromising quality or trust.

Please note this role as a new vacancy.

Salary Range

$120,000 - $145,000 CAD

At Riverside, we are committed to transparency and fairness in our compensation and job posting practices. The range above reflects the target compensation for the position at the time of posting. Exact compensation will be determined based on experience, skill set, education, and training, as well as other organizational needs, while balancing internal equity.

What We Offer:

• Values-led: We don’t cut corners or step on anyone or anything on our way to our summit. There is no winning at all costs here. Every step you take must align with our values, no compromises.
• Courageous determination: As a family-run, rapidly growing business, we are often challenged to find ways to deliver that aren’t obvious or easy. You must be willing to try, ask and answer challenging questions, test and learn, turn over every stone, keep moving forward and help us find a way through. Resourcefulness and grit will be your constant companions at Riverside and will serve you well.
• Humility: We’re a small (but growing) fish in a sea of whales and sharks. We know the products we offer are some of the healthiest and most sustainable, but we don’t brag about it, and know we have a steep path ahead. We pride ourselves in being respectful and supportive of others while shining brightly through our innovative, high-quality products. There isn’t one superstar at Riverside. We take turns leading the way as we climb to the summit.
• Continuous improvement: As a learn-as-we-go organization, we rely on each other to continuously improve everything we touch to make it better, more efficient, more sustainable, and more endearing to customers, consumers, employees, vendors, partners and the community. We own our mistakes and learn from them as we wind our way to the top.

Wait! There’s more!

• Immerse yourself in our comprehensive benefits program, with Riverside taking care of the costs!
• RRSP matching or 401k matching for an empowered financial journey
• Eligibility to participate in Riverside's Profit Sharing Plan
• Join Employee-Led Resource Groups (ERGs) championing mental health, sustainability, diversity, women, and LGBTQ+ rights
• Develop your career further through our Riverside University program and with our Tuition Reimbursement Program
• An open concept work environment that embodies our Values

How to Apply:

If you have the commitment to excellence, the energy, the attitude and experience we need, then please submit your resume to careers(AT)riversidenaturals.com with the job title you are applying for in the subject line or click the apply button!

Riverside Natural Foods Ltd. is committed to providing an inclusive and accessible environment for everyone. If you have a disability and require accommodation in the interview process, please let us know when you apply. We thank all applicants for their interest; however, due to volume, please note that only candidates selected for an interview will be contacted.

Disclaimer: As part of our recruitment process, we may use technology-assisted tools, including automated systems, to support the review and assessment of applications. These tools do not make final hiring decisions. All decisions related to screening, interviewing, and selection are made by our Talent Acquisition and hiring teams.