Analytics Engineer

Svitla Systems Inc. is looking for an Azure Data Architect with GenAI/RAG/Agentic АI Experience for a full-time position (40 hours per week) in Argentina. Our client operates a fleet of kiosk terminals running Windows 11 IoT Enterprise with a single Unity application in Shell Launcher kiosk mode. You will take the existing master image to a release-ready state and then support and maintain it. This is Windows systems and imaging work - the Unity application itself is built and maintained by another team and is out of scope.

The project focuses on delivering a scalable and governed data platform to support analytics and reporting needs. The solution involves onboarding diverse SQL and non-SQL data sources, defining and building data marts, and enabling Power BI reporting and dashboards.

As a Data Architect, you will take ownership of the enterprise Azure data architecture, including assessing and evolving an existing data platform that is only partially documented. The primary goal of the project is to define the required data marts and support the migration of the existing database to Snowflake while establishing a scalable, maintainable, and well-governed data foundation.

The role also involves designing the data architecture that supports RAG, GenAI, and Agentic AI applications. This includes defining how enterprise data and knowledge are ingested, prepared, stored, governed, and made available for retrieval and AI consumption. Hands-on development of RAG solutions or AI agents is not required.

Requirements

• Strong enterprise Azure Data Architecture experience with proven ownership of data architecture decisions.
• Experience taking ownership of an existing or legacy data platform, including assessing partially documented environments and separating tactical stabilization from long-term target architecture.
• Hands-on Azure Cosmos DB experience, including data modeling, partition-key strategy, indexing, RU/throughput and cost optimization, scaling, consistency, and Change Feed.
• Real-world production experience designing or contributing to the data architecture behind a RAG, GenAI, or Agentic AI application.
• Experience designing AI-ready data architectures and data layers for RAG, GenAI, and/or Agentic AI applications, including enterprise data and knowledge ingestion, preparation, storage, governance, and retrieval readiness.
• Strong and current experience with Azure Synapse Analytics, including Pipelines, Spark, Serverless SQL, and Dedicated SQL Pools.
• Strong understanding of where Synapse fits within an Azure data ecosystem and how it compares with Azure SQL, ADF, ADLS, Databricks, and Fabric.
• Experience with Azure Databricks for data engineering and data warehousing, combined with the ability to make technology-neutral architectural decisions.
• Experience with Azure SQL MI, SQL Server, and T-SQL.
• Experience designing Azure Data Lake/Lakehouse architectures.
• Experience with Azure Functions.
• Strong data modeling skills, including fact tables, dimensional/star schemas, and analytical model optimization.
• Strong experience with data ingestion design and data platform modernization.
• Experience designing end-to-end solutions for both structured and genuinely unstructured data, including documents, PDFs, scans, images, and emails.
• Experience designing metadata- and configuration-driven ingestion frameworks that support reusable and scalable onboarding of databases, APIs, and files.
• Ability to quickly assess an existing or legacy environment and produce concrete, actionable architecture recommendations within the first 1-2 weeks.
• Ability to work independently with incomplete information and deliver implementation-ready architectural outputs, including documentation, diagrams, and recommendations.
• Strong communication and stakeholder management skills, with the ability to align architectural decisions with both technical teams and business stakeholders.

Will be a plus

• Hands-on experience with document processing, OCR, text extraction, chunking, embeddings, or vector search/retrieval technologies as part of RAG-related data architecture.
• Familiarity with Microsoft Fabric and its positioning relative to Synapse and Databricks.
• Experience with dbt or similar data transformation frameworks as an alternative to Databricks-based ETL.

Responsibilities

• Own and evolve the enterprise Azure data architecture, including assessing and improving an existing, partially documented data platform.
• Design the data architecture and data layer supporting RAG, GenAI, and Agentic AI applications, including ingestion, preparation, storage, governance, and retrieval readiness of enterprise data and knowledge.
• Own Cosmos DB architecture decisions, including data modeling, partition-key strategy, indexing, RU/throughput and cost optimization, scaling, consistency, and Change Feed usage.
• Define and evolve the data architecture across Azure Synapse Analytics, Databricks, Azure SQL MI/SQL Server, Azure Data Lake/Lakehouse, and Azure Functions.
• Evaluate technology choices based on actual business needs, scalability, cost, and architectural value, avoiding unnecessary complexity.
• Separate tactical and short-term fixes from the long-term target architecture and provide implementation-ready documentation, diagrams, and recommendations.
• Design ingestion and processing solutions for both structured and unstructured data, including documents, PDFs, scans, images, and emails.
• Design metadata- and configuration-driven ingestion frameworks that enable new databases, APIs, and file-based sources to be onboarded efficiently and consistently.
• Assess existing and legacy environments and provide concrete, actionable architecture recommendations within the first 1-2 weeks.
• Communicate architectural decisions and align solutions with technical teams and business stakeholders.