SouthRivers Data

SouthRivers Data is a data & AI engineering partner. We strengthen the teams of consultancies and end clients across the EU, UK, and North America with senior data and AI engineers.

We're looking for an experienced Data Engineer to drive the development and maintenance of our data platform built on Azure. If you have strong hands-on experience with Databricks and Microsoft Fabric, we'd love to talk to you.

Responsibilities:

• Design, build, and maintain ETL/ELT pipelines using Azure Data Factory / Databricks
• Work with Microsoft Fabric: building data pipelines, lakehouse architecture, and semantic models
• Optimize performance and cost efficiency of data solutions on Azure
• Ensure data quality, reliability, and scalability across pipelines
• Collaborate with data analysts, ML engineers, and product teams to understand data requirements
• Contribute to data architecture design (data modeling, data governance)
• Conduct code reviews and mentor junior/mid-level engineers

Requirements:

• 3+ years of experience in Data Engineering
• Deep expertise in Azure (Data Factory, Synapse, Storage, Key Vault, etc.)
• Hands-on experience with Databricks (Spark, Delta Lake, Unity Catalog)
• Experience with Microsoft Fabric (Lakehouse, Data Pipelines, OneLake)
• Strong proficiency in SQL and Python (or Scala)
• Experience building and optimizing ETL/ELT processes
• Solid understanding of data modeling principles (dimensional modeling, star/snowflake schema)

Nice to Have:

• Experience with CI/CD for data pipelines (Azure DevOps, GitHub Actions)
• Knowledge of Power BI
• Experience in a regulated/enterprise environment
• Microsoft certifications (DP-203, Fabric Analytics Engineer, etc.)

SouthRivers Data is a data & AI engineering partner. We strengthen the teams of consultancies and end clients across the EU, UK, and North America with senior data and AI engineers.

We're looking for an AWS AI Architect with strong Agentic AI experience to join an AI PoC/MVP project for a large Canadian insurance company.

About the project:

• Design and build an AI PoC/MVP on AWS
• Focus on AI agents / agentic workflows and enterprise GenAI architecture
• Greenfield project with significant ownership over solution architecture and technology decisions
• Direct work with the client's English-speaking technical and business teams
• Full-time, long-term potential
• Location: Toronto / Canada — primarily remote, with a possibility of spending a few weeks onsite at the client's office

• Potential start date: September 15

   

Requirements:

• 6+ years in software, data, ML, or cloud engineering, with strong solution architecture experience
• Strong hands-on experience designing and building GenAI / Agentic AI solutions
• Solid AWS architecture experience
• Amazon Bedrock and related GenAI services
• Experience with AI agents: tool calling, orchestration, memory/state, multi-step workflows, and agent-to-system integrations
• Experience with at least one agent framework such as Strands Agents, LangGraph, CrewAI, LlamaIndex, or similar
• RAG architectures, embeddings, vector search, and knowledge retrieval
• Integration of LLMs/agents with enterprise APIs, databases, and internal systems
• Python and experience building production-grade AI services
• AWS services such as Lambda, S3, API Gateway, ECS/Fargate, IAM, CloudWatch
• Understanding of security, identity, access control, data privacy, and guardrails for enterprise AI systems
• Infrastructure as Code: Terraform or CloudFormation
• English B2+ — daily communication with the client, no interpreter

Nice to have:

• Amazon Bedrock AgentCore experience
• MCP / agent tool integration experience
• Multi-agent architectures
• Agent observability, evaluation, tracing, and production monitoring
• Amazon OpenSearch / vector databases
• Experience taking GenAI solutions from PoC to production
• Experience in insurance, financial services, or other regulated industries
• AWS certifications (Solutions Architect, Machine Learning, or similar)
• Canadian visa

Interview process:

1. Recruiter interview
2. Technical interview
3. Possible additional interview with an AWS / AI engineer