Data Engineer/ Architect

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

Design and own a canonical analytics data model that normalizes inputs from multiple accounting source systems into a unified, system-agnostic schema for downstream consumption Define and document a layered data architecture with clear boundaries and interface contracts between: source-aligned data models a canonical hub layer semantic or application-facing models Manage the end-to-end model lifecycle across

A large, regulated enterprise is hiring a data engineer to support a cloud-based pharmacy data warehouse used for ongoing reporting and analytics. This position focuses on maintaining and improving a mature data product with a broad user base and a large set of curated tables. The work blends hands-on development with investigation and stakeholder support,

A large enterprise team is seeking a data engineer to support the development and evolution of data‑driven rule‑based platforms. This role focuses on building, maintaining, and optimizing data pipelines and analytical systems that support advanced logic, automation, and machine learning use cases. The ideal candidate is hands‑on, adaptable, and able to deliver high‑quality work quickly