Remote Enterprise Data Architect - Lead Data Platform

Bright Vision Technologies

Sammamish (WA)

On-site

USD 100,000 - 150,000

Full time

3 days ago

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Job summary

Bright Vision Technologies is seeking an Enterprise Data Architect to lead the architecture of our enterprise data platform across ingestion, storage, processing, governance, and consumption layers. You will set standards for data modeling and lifecycle management, and partner with data engineering, analytics, ML, and business stakeholders to deliver a scalable data foundation.

The ideal candidate combines deep technical mastery with architectural judgment and has led data-platform programs of

Qualifications

Bachelor’s or Master’s degree in CS, IS, or a related field.
8+ years in data engineering with architecture roles.
Deep expertise across 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 across dimensional, normalized, and data vault patterns.
Experience implementing governance, lineage, and catalog capabilities.
Cloud, networking, identity, and cost optimization knowledge.
Excellent communication and stakeholder management.
Track record of leading large data platform initiatives across teams.

Responsibilities

Define the target-state architecture of the enterprise data platform, including ingestion, storage, processing, and consumption layers.
Establish standards for data modeling, schema evolution, partitioning, file formats, and storage organization.
Architect lakehouse, warehouse, and streaming patterns leveraging Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or Hudi.
Design end-to-end data pipelines balancing latency, cost, reliability, and maintainability across batch and streaming workloads.
Lead the integration of governance, lineage, and catalog tools such as Collibra, Alation, Atlan, Unity Catalog, or DataHub.
Define security architecture including row- and column-level controls, masking, encryption, and identity-aware access patterns.
Partner with ML, BI, and product teams to ensure platform capabilities align with downstream consumption needs.
Establish data contract and data product principles to drive ownership, quality, and decoupling between producers and consumers.
Lead architecture reviews and provide guidance on pipeline and warehouse design proposals across teams.
Drive cost optimization and capacity planning across the data platform estate.
Design disaster recovery, multi-region, and high-availability strategies for critical data assets.
Mentor data engineers and architects on platform standards and emerging best practice
Produce architecture artifacts including context diagrams, decision records, and reference patterns.
Stay current with data platform research, vendor offerings, and open-source ecosystem developments.