Remote Enterprise Data Architect - Platform & Governance Lead

Bright Vision Technologies

Highlands Ranch (CO)

Remote

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 for a fully remote role in the United States. The ideal candidate will define and lead the architecture of our enterprise data platform, spanning ingestion, storage, processing, governance, and consumption layers, and partner with data engineering, analytics, ML, and business stakeholders.

The role requires 6+ years of experience, deep expertise across lakehouse platforms, and a track record of large data initiatives.

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 architecture work.
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 expertise across dimensional, normalized, and data-vault patterns.
Experience implementing governance, lineage, and catalog capabilities.
Cloud platforms, networking, identity, and cost optimization knowledge.
Excellent communication and stakeholder management.
Track record of leading large data platform initiatives across teams.

Responsibilities

Define target-state architecture for the enterprise data platform across ingestion, storage, processing, and consumption layers.
Set standards for data modeling, schema evolution, partitioning, file formats, and storage organization.
Architect lakehouse, warehouse, and streaming patterns using modern tools and platforms.
Design end-to-end data pipelines balancing latency, cost, and reliability for batch and streaming workloads.
Lead governance, lineage, and catalog integration across teams and tools.
Define security architecture including row/column controls, masking, and identity-aware access.
Collaborate with ML, BI, and product teams to align platform capabilities with downstream needs.
Drive data product principles to ensure ownership, quality, and decoupling of producers/consumers.
Lead architecture reviews and provide guidance on pipeline and warehouse design proposals.
Drive cost optimization and capacity planning for the data platform estate.
Design disaster recovery, multi-region, and high-availability strategies for critical assets.
Mentor data engineers and architects on standards and best practices.
Produce architecture artifacts: context diagrams, decision records, reference patterns.