Data Engineer/ Architect

Job description A leading organization is seeking experienced data engineering contractors to support the modernization of a high-volume healthcare data platform. This initiative focuses on rebuilding a critical event processing system into a scalable, cloud-based architecture using modern data engineering tools and frameworks. The role involves working on a phased migration from a legacy system […]

Job description A leading organization is seeking a senior Snowflake platform engineer to own and evolve its enterprise cloud data platform. This role focuses on designing scalable data infrastructure, ensuring secure and governed data access, and enabling advanced analytics and artificial intelligence capabilities. The position combines hands-on engineering with platform ownership, requiring close collaboration with

Responsibilities Define and execute the data engineering roadmap, balancing new capabilities, platform stability, technical debt reduction, and cost management. Establish architectural standards, evaluate cloud services and tools, and build business cases for platform investments. Translate emerging capabilities within modern cloud data platforms into actionable engineering plans. Lead the design and ongoing operation of a medallion-style

Responsibilities Design and implement enterprise data governance architecture across modern data platforms, including Databricks, Collibra, cloud storage, business intelligence, and analytics environments. Define governance patterns for a Databricks Lakehouse environment, including Bronze, Silver, and Gold data layers, metadata standards, ownership models, lineage, access controls, data quality, retention, and certification. Partner with data engineering teams to

Responsibilities Define and implement enterprise ontologies, taxonomies, and controlled vocabularies aligned to core business domains Design a semantic context layer that connects structured data, metadata, and business meaning Establish patterns and standards for knowledge graph development and semantic modeling Align semantic architecture with an existing data platform, including Snowflake, and support emerging artificial intelligence and

Responsibilities Design and enhance enterprise-grade data platforms, including ingestion, transformation, storage, orchestration, and data serving layers for both batch and streaming use cases Build and maintain scalable data pipelines, reusable frameworks, and enterprise data models to support analytics, artificial intelligence, and operational reporting Define and manage semantic data layers while implementing governance controls such as

Responsibilities Design and develop end-to-end data pipelines using Python and SQL Build and maintain scalable data processing solutions to support underwriting and analytics needs Work with large datasets to ensure data quality, consistency, and reliability Collaborate with cross-functional teams to gather requirements and translate them into technical solutions Implement and manage data workflows using cloud-based

Responsibilities Build, enhance, and support scalable data pipelines across a cloud-based environment Develop data ingestion, transformation, and validation processes for batch and streaming workflows Write and maintain data transformation logic using Python and, when needed, SQL Configure and support scheduling and orchestration of pipelines using standard tooling Monitor pipeline performance, troubleshoot failures, and improve reliability

A leading organization is hiring a data engineer to build and support cloud-based data capabilities while also creating proof-of-concept prototypes that apply large language models and agent-style workflows to real business problems. This position blends strong data engineering fundamentals with practical experience prototyping AI solutions. The ideal candidate has hands-on experience building prototypes, not just