Remote Cloud Data Architect - Enterprise Platform Leader

Bright Vision Technologies; United States; À distance; USD 145 000 - 160 000; Plein temps

Résumé du poste

Bright Vision Technologies is seeking a Cloud Data Architect to define and lead the architecture of our enterprise data platform, spanning ingestion, storage, processing, governance, and consumption layers. The role drives the strategic direction of data infrastructure and partners with data engineering, analytics, ML, and business stakeholders to deliver a coherent, scalable data foundation.

The ideal candidate combines deep technical mastery of modern data platforms with strong architectural

Qualifications

• Eight or more years of experience in data engineering, with significant time in architecture roles.
• Deep expertise across at least two major data platforms such as Snowflake, Databricks, BigQuery, or Redshift.
• Strong understanding of lakehouse architectures, modern table formats, and streaming systems.
• Hands-on experience with Spark, Flink, or Kafka at production scale.
• Strong data modeling expertise across dimensional, normalized, and data-vault patterns.
• Experience implementing governance, lineage, and catalog capabilities.
• Solid grasp of cloud platforms, networking, identity, and cost optimization.
• Excellent communication, facilitation, and stakeholder management skills.
• Track record of leading large data platform initiatives across teams.

Connaissances

Data engineering

Data architecture

Cloud data platforms

Lakehouse architecture

Streaming systems

Data modeling

Governance & lineage

Cloud fundamentals

Stakeholder management

Description du poste

Bright Vision Technologies is seeking a Cloud Data Architect to define and lead the architecture of our enterprise data platform, spanning ingestion, storage, processing, governance, and consumption layers. The role drives the strategic direction of data infrastructure and partners with data engineering, analytics, ML, and business stakeholders to deliver a coherent, scalable data foundation.

The ideal candidate combines deep technical mastery of modern data platforms with strong architectural