Remote Cloud Data Architect — Lead Data Platform

Bright Vision Technologies; Cedar Park (TX); Remote; USD 145,000 - 160,000; Full time

Job summary

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, sets standards for data modeling and lifecycle management, and partners with data engineering, analytics, ML, and business stakeholders to deliver a coherent, scalable data foundation.

Qualifications

• Eight or more years of experience in data engineering, with architecture roles.
• Deep expertise across Snowflake, Databricks, BigQuery, or Redshift.
• Strong knowledge of lakehouse architectures, modern table formats, and streaming systems.
• Hands-on experience with Spark, Flink, or Kafka at production scale.
• Strong data modeling 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.

Responsibilities

• Define and lead the architecture of the enterprise data platform.
• Drive the strategic direction of data infrastructure, governance, and lifecycle management.
• Partner with data engineering, analytics, ML, and business stakeholders to deliver a scalable data foundation.

Skills

Data architecture

Data engineering

Spark/Flink/Kafka

Data modeling

Cloud platforms

Stakeholder management

Communication

Leadership

Tools

Snowflake

Databricks

BigQuery

Redshift

Job description

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, sets standards for data modeling and lifecycle management, and partners with data engineering, analytics, ML, and business stakeholders to deliver a coherent, scalable data foundation.