Remote Data Solutions Architect - Lead Data Platform

Bright Vision Technologies; Elk Grove (CA); Remote; USD 150,000 - 180,000; Full time

Job summary

Bright Vision Technologies is seeking a Data Solutions 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

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
• 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.

Responsibilities

• Define and lead the architecture of our enterprise data platform, spanning ingestion, storage, processing, governance, and consumption layers.
• Partner with data engineering, analytics, ML, and business stakeholders to deliver a coherent, scalable data foundation.
• Set standards for data modeling and lifecycle management and drive architectural governance.

Job description

Bright Vision Technologies is seeking a Data Solutions 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.