Senior Data Engineer

- Proficiency in diagramming and process mapping tools such as Visio and Miro - Strong SQL skills and experience with Python or Scala for data engineering tasks - Solid understanding of data modeling principles (relational, dimensional, and graph-based)

- Experience with SPARQL query language for RDF data - Familiarity with additional Azure data services — Azure SQL Database, Microsoft Fabric, Azure Event Hubs - Experience integrating semantic/graph data with AI, ML, or GenAI applications, particularly via Azure OpenAI Service

Blanc Labs is a premier partner for global enterprises, leading the way in digitization, automation, and the development of next-generation digital products and services. Our expertise in digital transformation powers businesses to accelerate service delivery, drive customer engagement, and foster growth. We are seeking a highly skilled Senior Data Engineer with expertise in modern data platforms and semantic technologies to design and build scalable data solutions that power enterprise analytics and knowledge representation. This role sits within a Microsoft Azure environment, and combines strong data engineering fundamentals with specialized experience in graph databases, ontologies, and semantic modeling to help the organization structure and connect complex data across domains. What You'll be Doing:

What You'll be Doing: - Design, build, and maintain scalable data pipelines and lakehouse architectures using Azure Databricks - Implement and manage data governance, access control, and lineage using Unity Catalog, aligned with Microsoft Purview

- Build and maintain knowledge graphs using RDF (Resource Description Framework) and OWL (Web Ontology Language) standards - Design and implement graph database solutions using Neo4j to support relationship-driven data use cases, deployed on Azure infrastructure - Develop ontologies and taxonomies to enable consistent data interpretation across systems

- Translate business processes and data relationships into architecture diagrams using Visio and Miro - Collaborate with data architects, analysts, and business stakeholders to align data models with organizational needs across the Microsoft data ecosystem (Azure Synapse, Microsoft Fabric) - Optimize data pipelines for performance, reliability, and scalability using Azure Data Factory and Databricks Workflows

- Collaborate with data architects, analysts, and business stakeholders to align data models with organizational needs across the Microsoft data ecosystem (Azure Synapse, Microsoft Fabric) - Optimize data pipelines for performance, reliability, and scalability using Azure Data Factory and Databricks Workflows - Ensure data quality, consistency, and integrity across ingestion, transformation, and storage layers, including Azure Data Lake Storage (ADLS Gen2) and Delta Lake

- Optimize data pipelines for performance, reliability, and scalability using Azure Data Factory and Databricks Workflows - Ensure data quality, consistency, and integrity across ingestion, transformation, and storage layers, including Azure Data Lake Storage (ADLS Gen2) and Delta Lake - Support integration of semantic and graph-based data models with downstream analytics and AI/ML applications, including Azure OpenAI Service and Azure AI Studio where applicable

- Ensure data quality, consistency, and integrity across ingestion, transformation, and storage layers, including Azure Data Lake Storage (ADLS Gen2) and Delta Lake - Support integration of semantic and graph-based data models with downstream analytics and AI/ML applications, including Azure OpenAI Service and Azure AI Studio where applicable - Document data architecture, pipelines, and semantic models for cross-team visibility and maintainability

- 8+ years of experience in data engineering, with a strong foundation in building production-grade data pipelines - Required: Hands-on experience with the Microsoft Azure data stack — Azure Databricks, Azure Synapse Analytics, and/or Azure Data Factory in production environments - Hands-on experience with Databricks for data processing, transformation, and analytics workloads

- Familiarity with additional Azure data services — Azure SQL Database, Microsoft Fabric, Azure Event Hubs - Experience integrating semantic/graph data with AI, ML, or GenAI applications, particularly via Azure OpenAI Service - Knowledge of metadata management and enterprise data governance frameworks, including Microsoft Purview

- Knowledge of metadata management and enterprise data governance frameworks, including Microsoft Purview - Microsoft certifications (e.g., Azure Data Engineer Associate, Fabric Analytics Engineer Associate) considered a strong plus - Experience working in Agile/Scrum environments

- Required: Hands-on experience with the Microsoft Azure data stack — Azure Databricks, Azure Synapse Analytics, and/or Azure Data Factory in production environments - Hands-on experience with Databricks for data processing, transformation, and analytics workloads - Experience implementing data governance and cataloging using Unity Catalog

- Practical experience with RDF and OWL for knowledge representation and ontology development - Hands-on experience with Neo4j or other graph database technologies - Experience designing semantic models and understanding of graph theory concepts