Remote Cloud Data Architect - Enterprise Data Platform Lead

Bright Vision Technologies; Euless, Bedford (TX, TX); On-site; 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 focus.
• Deep expertise across Snowflake, Databricks, BigQuery, or Redshift.
• Knowledge of lakehouse architectures, table formats, and streaming systems.
• Hands-on with Spark, Flink, or Kafka at production scale.
• Strong data modeling across dimensional, normalized, and data-vault patterns.
• Experience with governance, lineage, and catalog capabilities.
• Understanding of cloud platforms, networking, identity, and cost optimization.
• Excellent communication and stakeholder management.

Responsibilities

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

Skills

Data engineering

Data architecture

Data modeling

Governance

Lakehouse

Spark/Kafka

Stakeholder management

Cloud platforms

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.