Senior Data Platform Engineer

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.

Responsibilities

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; 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; 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; 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; 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; 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; 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

Requirements

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; Strong SQL and Python for data engineering; Strong hands-on experience with Databricks; 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; 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; 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

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

Benefits

Comprehensive benefits program with Riverside taking care of the costs; RRSP matching or 401k matching; Eligibility to participate in Riverside's Profit Sharing Plan; Employee-Led Resource Groups (ERGs) championing mental health, sustainability, diversity, women, and LGBTQ+ rights; Riverside University program; Tuition Reimbursement Program; Open concept work environment