Azure Data Architect (GenAI/RAG/Agentic)
New
S
Svitla Systems Inc.Data architecture
Full-time position (40 hours per week) in EuropeFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years of professional experience in Data Engineering
- Required Skills
- Microsoft SQL ServerData engineering
Requirements
- Have 8+ years of professional Data Engineering experience, with strong enterprise data architecture experience and architecture ownership.
- Bring hands-on Azure Cosmos DB experience with data modeling, partition-key strategy, indexing, RU/throughput and cost optimization, scaling, consistency, and Change Feed.
- Have personally designed or contributed to the data architecture of a production RAG, GenAI, or Agentic AI application.
- Have experience designing AI-ready data architecture and data layers for ingestion, preparation, storage, governance, and retrieval readiness.
- Demonstrate enterprise Azure Data Architecture ownership, including legacy-platform stabilization and technology evaluation based on scale, cost, and business need.
- Have current Azure Synapse Analytics experience across Pipelines, Spark, Serverless SQL, and Dedicated SQL Pools.
- Have Azure Databricks experience in data engineering and data warehousing, with the ability to make technology-neutral recommendations.
- Have experience with Azure SQL MI, SQL Server, and T-SQL.
- Have experience with Azure Data Lake or Lakehouse architecture and Azure Functions.
- Have strong data modeling experience, including fact tables, dimensional/star schemas, and analytical model optimization.
- Have experience with structured and unstructured data, including documents, PDFs, scans, images, and emails.
- Have experience with metadata/configuration-driven ingestion and scalable, reusable data-platform design.
- Be able to independently assess an undocumented platform and produce an actionable architecture plan within 1–2 weeks, working with incomplete information.
- Communicate effectively with technical and business stakeholders.
Responsibilities
- Own and evolve the enterprise Azure data architecture, including assessing an existing, partially documented data platform.
- Design the data layer for GenAI, RAG, and/or Agentic AI applications, including enterprise data ingestion, preparation, storage, governance, and retrieval readiness.
- Own Cosmos DB architecture decisions covering data modeling, partition keys, indexing, throughput and cost optimization, scaling, consistency, and Change Feed.
- Define data architecture across Azure Synapse Analytics, Databricks, Azure SQL MI/SQL Server, Data Lake/Lakehouse, and Azure Functions.
- Separate tactical fixes from long-term target architecture and produce implementation-ready documentation, diagrams, and recommendations.
- Design ingestion and processing for structured and unstructured data, including documents, PDFs, scans, images, and emails.
- Design a metadata- and configuration-driven reusable ingestion framework for onboarding databases, APIs, and files.
- Assess existing or legacy environments and deliver actionable architecture recommendations within the first 1–2 weeks.
- Communicate and align architectural decisions with technical teams and business stakeholders.
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