Enterprise Data & Generative AI Engineer

Riverside Natural Foods Ltd. • San Francisco, CA

8h

About The Position

As Riverside Natural Foods continues its business transformation journey, we are investing in leading-edge data and analytics capabilities to support long-term, values-based growth. A key pillar of this transformation is the evolution of a trusted data ecosystem as a foundation for our Business Intelligence and AI strategy.
The Enterprise Data & Generative AI Engineer plays a central role in building and operating the data foundation that powers analytics, machine learning, and Generative AI across the organization. This role spans cloud lakehouse platforms (Databricks or Snowflake), syndicated commercial 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 must be a self-starter with strong communication skills, a positive outlook, curiosity, and a deep understanding of SAP-centric enterprise data architecture with other modern lakehouse data ecosystems.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
• 5+ years of CPG experience in Business Intelligence, Data Engineering, or Analytics roles preferred.
• Prior work integrating SAP with cloud lakehouse platforms.
• 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.
• 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 preferred.
• 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.
• Knowledge of streaming technologies (Kafka, Kinesis, or equivalent).
• Experience building pipelines for unstructured data (documents, images, logs).
• Familiarity with vector databases (FAISS, Pinecone, Weaviate, or cloud-native equivalents).
• Understanding of LLMs, embeddings, and RAG architectures preferred.
• Exposure to ML lifecycle tooling (MLflow, SageMaker, Vertex AI, or Databricks ML).
• Ability to support model monitoring and AI observability preferred.
• You are proactive, energetic, and bring joy to the teams you work with.
• You naturally take ownership and have a can-do attitude.
• You are highly organized, detail-oriented, and love solving problems.
• 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.
• You are a self-starter and thrive in a collaborative, fast-paced, and values-driven environment.
• 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.

Responsibilities

• Data Integration & Pipeline Engineering
• 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.
• Support the reliable delivery of current reports consumed by the business and 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 (emerging area)
• 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
• Cross-Functional Collaboration
• Partner with key resources in BT&T and business stakeholders to understand priorities and translate business requirements into scalable data solutions that support analytics and GenAI use cases.
• Provide technical guidance on data architecture decisions involving SAP Datasphere, Databricks, Snowflake, and IoT/OT data platforms.
• Be a Riverside Brand Ambassador: Stay relentlessly close to our consumers and represent the brand in every interaction, decision, and deliverable. Bring the consumer voice into your work by protecting product quality, availability, and experience, acting early when standards slip, and delivering consistent value that earns trust, advocacy, and long-term brand love.

Benefits

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 101-250 employees